A theoretical framework for gene induction and experimental comparisons

Anticipating response function in gene regulatory networks

The origin of an ordered genetic response of a complex and noisy biological cell is intimately related to the detailed mechanism of protein-DNA interactions present in a wide variety of gene regulatory (GR) systems. However, the quantitative prediction of genetic response and the correlation between the mechanism and the response curve is poorly understood. Here, we report in silico binding studies of GR systems to show that the transcription factor (TF) binds to multiple DNA sites with high cooperativity spreads from specific binding sites into adjacent non-specific DNA and bends the DNA. Our analysis is not limited only to the isolated model system but also can be applied to a system containing multiple interacting genes. The controlling role of TF oligomerization, TF-ligand interactions, and DNA looping for gene expression has been also characterized. The predictions are validated against detailed grand canonical Monte Carlo simulations and published data for the lac operon system. Overall, our study reveals that the expression of target genes can be quantitatively controlled by modulating TF-ligand interactions and the bending energy of DNA.

Dissecting transcriptional amplification by MYC

Supraphysiological MYC levels are oncogenic. Originally considered a typical transcription factor recruited to E-boxes (CACGTG), another theory posits MYC a global amplifier increasing output at all active promoters. Both models rest on large-scale genome-wide "-omics'. Because the assumptions, statistical parameter and model choice dictates the '-omic' results, whether MYC is a general or specific transcription factor remains controversial. Therefore, an orthogonal series of experiments interrogated MYC's effect on the expression of synthetic reporters. Dose-dependently, MYC increased output at minimal promoters with or without an E-box. Driving minimal promoters with exogenous (glucocorticoid receptor) or synthetic transcription factors made expression more MYC-responsive, effectively increasing MYC-amplifier gain. Mutations of conserved MYC-Box regions I and II impaired amplification, whereas MYC-box III mutations delivered higher reporter output indicating that MBIII limits over-amplification. Kinetic theory and experiments indicate that MYC activates at least two steps in the transcription-cycle to explain the non-linear amplification of transcription that is essential for global, supraphysiological transcription in cancer.

Glucocorticoid and Mineralocorticoid Receptors in the Brain: A Transcriptional Perspective

Adrenal glucocorticoid hormones are crucial for maintenance of homeostasis and adaptation to stress. They act via the mineralocorticoid receptors (MRs) and glucocorticoid receptors (GRs)-members of the family of nuclear receptors. MRs and GRs can mediate distinct, sometimes opposite, effects of glucocorticoids. Both receptor types can mediate nongenomic steroid effects, but they are best understood as ligand-activated transcription factors. MR and GR protein structure is similar; the receptors can form heterodimers on the DNA at glucocorticoid response elements (GREs), and they share a number of target genes. The transcriptional basis for opposite effects on cellular physiology remains largely unknown, in particular with respect to MR-selective gene transcription. In this review, we discuss proven and potential mechanisms of transcriptional specificity for MRs and GRs. These include unique GR binding to "negative GREs," direct binding to other transcription factors, and binding to specific DNA sequences in conjunction with other transcription factors, as is the case for MRs and NeuroD proteins in the brain. MR- and GR-specific effects may also depend on specific interactions with transcriptional coregulators, downstream mediators of transcriptional receptor activity. Current data suggest that the relative importance of these mechanisms depends on the tissue and physiological context. Insight into these processes may not only allow a better understanding of homeostatic regulation but also the development of drugs that target specific aspects of disease.

GR Dimerization and the Impact of GR Dimerization on GR Protein Stability and Half-Life

Pharmacologically, glucocorticoids, which mediate their effects via the glucocorticoid receptor (GR), are a most effective therapy for inflammatory diseases despite the fact that chronic use causes side-effects and acquired GC resistance. The design of drugs with fewer side-effects and less potential for the development of resistance is therefore considered crucial for improved therapy. Dimerization of the GR is an integral step in glucocorticoid signaling and has been identified as a possible molecular site to target for drug development of anti-inflammatory drugs with an improved therapeutic index. Most of the current understanding regarding the role of GR dimerization in GC signaling derives for dimerization deficient mutants, although the role of ligands biased toward monomerization has also been described. Even though designing for loss of dimerization has mostly been applied for reduction of side-effect profile, designing for loss of dimerization may also be a fruitful strategy for the development of GC drugs with less potential to develop GC resistance. GC-induced resistance affects up to 30% of users and is due to a reduction in the GR functional pool. Several molecular mechanisms of GC-mediated reductions in GR pool have been described, one of which is the autologous down-regulation of GR density by the ubiquitin-proteasome-system (UPS). Loss of GR dimerization prevents autologous down-regulation of the receptor through modulation of interactions with components of the UPS and post-translational modifications (PTMs), such as phosphorylation, which prime the GR for degradation. Rational design of conformationally biased ligands that select for a monomeric GR conformation, which increases GC sensitivity through improving GR protein stability and increasing half-life, may be a productive avenue to explore. However, potential drawbacks to this approach should be considered as well as the advantages and disadvantages in chronic vs. acute treatment regimes.

A Model of Glucocorticoid Receptor Interaction With Coregulators Predicts Transcriptional Regulation of Target Genes

Regulatory factors that control gene transcription in multicellular organisms are assembled in multicomponent complexes by combinatorial interactions. In this context, nuclear receptors provide well-characterized and physiologically relevant systems to study ligand-induced transcription resulting from the integration of cellular and genomic information in a cell- and gene-specific manner. Here, we developed a mathematical model describing the interactions between the glucocorticoid receptor (GR) and other components of a multifactorial regulatory complex controlling the transcription of GR-target genes, such as coregulator peptides. We support the validity of the model in relation to gene-specific GR transactivation with gene transcription data from A549 cells and in vitro real time quantification of coregulator-GR interactions. The model accurately describes and helps to interpret ligand-specific and gene-specific transcriptional regulation by the GR. The comprehensive character of the model allows future insight into the function and relative contribution of the molecular species proposed in ligand- and gene-specific transcriptional regulation.

Structural conditions on complex networks for the Michaelis-Menten input-output response

The Michaelis-Menten (MM) fundamental formula describes how the rate of enzyme catalysis depends on substrate concentration. The familiar hyperbolic relationship was derived by timescale separation for a network of three reactions. The same formula has subsequently been found to describe steady-state input-output responses in many biological contexts, including single-molecule enzyme kinetics, gene regulation, transcription, translation, and force generation. Previous attempts to explain its ubiquity have been limited to networks with regular structure or simplifying parametric assumptions. Here, we exploit the graph-based linear framework for timescale separation to derive general structural conditions under which the MM formula arises. The conditions require a partition of the graph into two parts, akin to a "coarse graining" into the original MM graph, and constraints on where and how the input variable occurs. Other features of the graph, including the numerical values of parameters, can remain arbitrary, thereby explaining the formula's ubiquity. For systems at thermodynamic equilibrium, we derive a necessary and sufficient condition. For systems away from thermodynamic equilibrium, especially those with irreversible reactions, distinct structural conditions arise and a general characterization remains open. Nevertheless, our results accommodate, in much greater generality, all examples known to us in the literature.

Transcription factor target site search and gene regulation in a background of unspecific binding sites

Response time and transcription level are vital parameters of gene regulation. They depend on how fast transcription factors (TFs) find and how efficient they occupy their specific target sites. It is well known that target site search is accelerated by TF binding to and sliding along unspecific DNA and that unspecific associations alter the occupation frequency of a gene. However, whether target site search time and occupation frequency can be optimized simultaneously is mostly unclear. We developed a transparent and intuitively accessible state-based formalism to calculate search times to target sites on and occupation frequencies of promoters of arbitrary state structure. Our formalism is based on dissociation rate constants experimentally accessible in live cell experiments. To demonstrate our approach, we consider promoters activated by a single TF, by two coactivators or in the presence of a competitive inhibitor. We find that target site search time and promoter occupancy differentially vary with the unspecific dissociation rate constant. Both parameters can be harmonized by adjusting the specific dissociation rate constant of the TF. However, while measured DNA residence times of various eukaryotic TFs correspond to a fast search time, the occupation frequencies of target sites are generally low. Cells might tolerate low target site occupancies as they enable timely gene regulation in response to a changing environment.

An Approach to Greater Specificity for Glucocorticoids

Glucocorticoid steroids are among the most prescribed drugs each year. Nonetheless, the many undesirable side effects, and lack of selectivity, restrict their greater usage. Research to increase glucocorticoid specificity has spanned many years. These efforts have been hampered by the ability of glucocorticoids to both induce and repress gene transcription and also by the lack of success in defining any predictable properties that control glucocorticoid specificity. Correlations of transcriptional specificity have been observed with changes in steroid structure, receptor and chromatin conformation, DNA sequence for receptor binding, and associated cofactors. However, none of these studies have progressed to the point of being able to offer guidance for increased specificity. We summarize here a mathematical theory that allows a novel and quantifiable approach to increase selectivity. The theory applies to all three major actions of glucocorticoid receptors: induction by agonists, induction by antagonists, and repression by agonists. Simple graphical analysis of competition assays involving any two factors (steroid, chemical, peptide, protein, DNA, etc.) yields information (1) about the kinetically described mechanism of action for each factor at that step where the factor acts in the overall reaction sequence and (2) about the relative position of that step where each factor acts. These two pieces of information uniquely provide direction for increasing the specificity of glucocorticoid action. Consideration of all three modes of action indicate that the most promising approach for increased specificity is to vary the concentrations of those cofactors/pharmaceuticals that act closest to the observed end point. The potential for selectivity is even greater when varying cofactors/pharmaceuticals in conjunction with a select class of antagonists.

Inferring gene regulatory networks from single-cell data: a mechanistic approach

Background

The recent development of single-cell transcriptomics has enabled gene expression to be measured in individual cells instead of being population-averaged. Despite this considerable precision improvement, inferring regulatory networks remains challenging because stochasticity now proves to play a fundamental role in gene expression. In particular, mRNA synthesis is now acknowledged to occur in a highly bursty manner.

Results

We propose to view the inference problem as a fitting procedure for a mechanistic gene network model that is inherently stochastic and takes not only protein, but also mRNA levels into account. We first explain how to build and simulate this network model based upon the coupling of genes that are described as piecewise-deterministic Markov processes. Our model is modular and can be used to implement various biochemical hypotheses including causal interactions between genes. However, a naive fitting procedure would be intractable. By performing a relevant approximation of the stationary distribution, we derive a tractable procedure that corresponds to a statistical hidden Markov model with interpretable parameters. This approximation turns out to be extremely close to the theoretical distribution in the case of a simple toggle-switch, and we show that it can indeed fit real single-cell data. As a first step toward inference, our approach was applied to a number of simple two-gene networks simulated in silico from the mechanistic model and satisfactorily recovered the original networks.

Conclusions

Our results demonstrate that functional interactions between genes can be inferred from the distribution of a mechanistic, dynamical stochastic model that is able to describe gene expression in individual cells. This approach seems promising in relation to the current explosion of single-cell expression data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0487-0) contains supplementary material, which is available to authorized users.

Unconventional Coupling between Ligand Recognition and Allosteric Control in the Multidrug Resistance Gene Regulator, BmrR

BmrR is a multidrug resistance (MDR) regulator that responds to diverse ligands. To obtain insight into signal recognition, allosteric control, and cooperativity, we used a quantitative in vitro transcription assay to determine the ligand-dependent activation profiles for a diverse set of cations, zwitterions, and uncharged ligands. As for many other biological switch systems, the data are well described by a modified Hill equation. Parameters extracted from curve fits to the data include L₅₀ , R_MAX and N. We found that L₅₀ values correlate directly with ΔG_BIND values, suggesting that the parameter reflects binding, whereas R_MAX and N reflect allosteric control and cooperativity, respectively. Our results suggest unconventional coupling between ligand binding and allosteric control, with weakly interacting ligands exhibiting the highest levels of activation. Such properties are in stark contrast to those often exhibited by biological switch proteins, whereby ligand binding and allostery are tightly coupled, yielding both high selectivity and ultrasensitivity. We propose that weakened coupling, as observed for BmrR, may be important for providing robust activation responses to unrelated ligands. We also propose that other MDR proteins and other polyspecific switch systems will show similar features.

Glucocorticoid Signaling: An Update from a Genomic Perspective

Glucocorticoid hormones (GC) regulate essential physiological functions including energy homeostasis, embryonic and postembryonic development, and the stress response. From the biomedical perspective, GC have garnered a tremendous amount of attention as highly potent anti-inflammatory and immunosuppressive medications indispensable in the clinic. GC signal through the GC receptor (GR), a ligand-dependent transcription factor whose structure, DNA binding, and the molecular partners that it employs to regulate transcription have been under intense investigation for decades. In particular, next-generation sequencing-based approaches have revolutionized the field by introducing a unified platform for a simultaneous genome-wide analysis of cellular activities at the level of RNA production, binding of transcription factors to DNA and RNA, and chromatin landscape and topology. Here we describe fundamental concepts of GC/GR function as established through traditional molecular and in vivo approaches and focus on the novel insights of GC biology that have emerged over the last 10 years from the rapidly expanding arsenal of system-wide genomic methodologies.

More than meets the dimer: What is the quaternary structure of the glucocorticoid receptor?

It is widely accepted that the glucocorticoid receptor (GR), a ligand-regulated transcription factor that triggers anti-inflammatory responses, binds specific response elements as a homodimer. Here, we will discuss the original primary data that established this model and contrast it with a recent report characterizing the GR-DNA complex as a tetramer.

Competitive Agonists and Antagonists of Steroid Nuclear Receptors: Evolution of the Concept or Its Reversal

The mechanisms displaying pure and mixed steroid agonist/antagonist activity as well as principles underlying in vivo action of selective steroid receptor modulators dependent on tissue or cell type including interaction with various types of nuclear receptors are analyzed in this work. Mechanisms of in vitro action for mixed agonist/antagonist steroids are discussed depending on: specific features of their interaction with receptor hormone-binding pocket; steroid-dependent allosteric modulation of interaction between hormone-receptor complex and hormone response DNA elements; features of interacting hormone-receptor complex with protein transcriptional coregulators; level and tissue-specific composition of transcriptional coregulators. A novel understanding regarding context-selective modulators replacing the concept of steroid agonists and antagonists is discussed.

Glucocorticoid-independent modulation of GR activity: Implications for immunotherapy

Pharmacological doses of glucocorticoids (GCs), acting via the glucocorticoid receptor (GR) to repress inflammation and immune function, remain the most effective therapy in the treatment of inflammatory and immune diseases. Since many patients on GC therapy exhibit GC resistance and severe side-effects, much research is focused on developing more selective GCs and combination therapies, with greater anti-inflammatory potency. GCs mediate their classical genomic transcriptional effects by binding to the cytoplasmic GR, followed by nuclear translocation and modulation of transcription of target genes by direct DNA binding of the GR or its tethering to other transcription factors. Recent evidence suggests, however, that the responses mediated by the GR are much more complex and involve multiple parallel mechanisms integrating simultaneous signals from other receptors, both in the absence and presence of GCs, to shift the sensitivity of a target cell to GCs. The level of cellular stress, immune activation status, or the cell cycle phase may be crucial for determining GC sensitivity and GC responsiveness as well as subcellular localization of the GR and GR levels. Central to the development of new drugs that target GR signaling alone or as add-on therapies, is an in-depth understanding of the molecular mechanisms of GC-independent GR desensitization, priming and activation of the unliganded GR, as well as synergy and cross-talk with other signaling pathways. This review will discuss the information currently available on these topics and their relevance to immunotherapy, as well as identify unanswered questions and future areas of research.

Kinetically Defined Mechanisms and Positions of Action of Two New Modulators of Glucocorticoid Receptor-regulated Gene Induction

Most of the steps in, and many of the factors contributing to, glucocorticoid receptor (GR)-regulated gene induction are currently unknown. A competition assay, based on a validated chemical kinetic model of steroid hormone action, is now used to identify two new factors (BRD4 and negative elongation factor (NELF)-E) and to define their sites and mechanisms of action. BRD4 is a kinase involved in numerous initial steps of gene induction. Consistent with its complicated biochemistry, BRD4 is shown to alter both the maximal activity (Amax) and the steroid concentration required for half-maximal induction (EC50) of GR-mediated gene expression by acting at a minimum of three different kinetically defined steps. The action at two of these steps is dependent on BRD4 concentration, whereas the third step requires the association of BRD4 with P-TEFb. BRD4 is also found to bind to NELF-E, a component of the NELF complex. Unexpectedly, NELF-E modifies GR induction in a manner that is independent of the NELF complex. Several of the kinetically defined steps of BRD4 in this study are proposed to be related to its known biochemical actions. However, novel actions of BRD4 and of NELF-E in GR-controlled gene induction have been uncovered. The model-based competition assay is also unique in being able to order, for the first time, the sites of action of the various reaction components: GR < Cdk9 < BRD4 ≤ induced gene < NELF-E. This ability to order factor actions will assist efforts to reduce the side effects of steroid treatments.

A model for aryl hydrocarbon receptor-activated gene expression shows potency and efficacy changes and predicts squelching due to competition for transcription co-activators

A stochastic model of nuclear receptor-mediated transcription was developed based on activation of the aryl hydrocarbon receptor (AHR) by 2,3,7,8-tetrachlorodibenzodioxin (TCDD) and subsequent binding the activated AHR to xenobiotic response elements (XREs) on DNA. The model was based on effects observed in cells lines commonly used as in vitro experimental systems. Following ligand binding, the AHR moves into the cell nucleus and forms a heterodimer with the aryl hydrocarbon nuclear translocator (ARNT). In the model, a requirement for binding to DNA is that a generic coregulatory protein is subsequently bound to the AHR-ARNT dimer. Varying the amount of coregulator available within the nucleus altered both the potency and efficacy of TCDD for inducing for transcription of CYP1A1 mRNA, a commonly used marker for activation of the AHR. Lowering the amount of available cofactor slightly increased the EC50 for the transcriptional response without changing the efficacy or maximal response. Further reduction in the amount of cofactor reduced the efficacy and produced non-monotonic dose-response curves (NMDRCs) at higher ligand concentrations. The shapes of these NMDRCs were reminiscent of the phenomenon of squelching. Resource limitations for transcriptional machinery are becoming apparent in eukaryotic cells. Within single cells, nuclear receptor-mediated gene expression appears to be a stochastic process; however, intercellular communication and other aspects of tissue coordination may represent a compensatory process to maintain an organism’s ability to respond on a phenotypic level to various stimuli within an inconstant environment.

Kinetically-defined component actions in gene repression

Gene repression by transcription factors, and glucocorticoid receptors (GR) in particular, is a critical, but poorly understood, physiological response. Among the many unresolved questions is the difference between GR regulated induction and repression, and whether transcription cofactor action is the same in both. Because activity classifications based on changes in gene product level are mechanistically uninformative, we present a theory for gene repression in which the mechanisms of factor action are defined kinetically and are consistent for both gene repression and induction. The theory is generally applicable and amenable to predictions if the dose-response curve for gene repression is non-cooperative with a unit Hill coefficient, which is observed for GR-regulated repression of AP1LUC reporter induction by phorbol myristate acetate. The theory predicts the mechanism of GR and cofactors, and where they act with respect to each other, based on how each cofactor alters the plots of various kinetic parameters vs. cofactor. We show that the kinetically-defined mechanism of action of each of four factors (reporter gene, p160 coactivator TIF2, and two pharmaceuticals [NU6027 and phenanthroline]) is the same in GR-regulated repression and induction. What differs is the position of GR action. This insight should simplify clinical efforts to differentially modulate factor actions in gene induction vs. gene repression.

Theory of partial agonist activity of steroid hormones

The different amounts of residual partial agonist activity (PAA) of antisteroids under assorted conditions have long been useful in clinical applications but remain largely unexplained. Not only does a given antagonist often afford unequal induction for multiple genes in the same cell but also the activity of the same antisteroid with the same gene changes with variations in concentration of numerous cofactors. Using glucocorticoid receptors as a model system, we have recently succeeded in constructing from first principles a theory that accurately describes how cofactors can modulate the ability of agonist steroids to regulate both gene induction and gene repression. We now extend this framework to the actions of antisteroids in gene induction. The theory shows why changes in PAA cannot be explained simply by differences in ligand affinity for receptor and requires action at a second step or site in the overall sequence of reactions. The theory also provides a method for locating the position of this second site, relative to a concentration limited step (CLS), which is a previously identified step in glucocorticoid-regulated transactivation that always occurs at the same position in the overall sequence of events of gene induction. Finally, the theory predicts that classes of antagonist ligands may be grouped on the basis of their maximal PAA with excess added cofactor and that the members of each class differ by how they act at the same step in the overall gene induction process. Thus, this theory now makes it possible to predict how different cofactors modulate antisteroid PAA, which should be invaluable in developing more selective antagonists.

A framework for modelling gene regulation which accommodates non-equilibrium mechanisms

BACKGROUND

Gene regulation has, for the most part, been quantitatively analysed by assuming that regulatory mechanisms operate at thermodynamic equilibrium. This formalism was originally developed to analyse the binding and unbinding of transcription factors from naked DNA in eubacteria. Although widely used, it has made it difficult to understand the role of energy-dissipating, epigenetic mechanisms, such as DNA methylation, nucleosome remodelling and post-translational modification of histones and co-regulators, which act together with transcription factors to regulate gene expression in eukaryotes.

RESULTS

Here, we introduce a graph-based framework that can accommodate non-equilibrium mechanisms. A gene-regulatory system is described as a graph, which specifies the DNA microstates (vertices), the transitions between microstates (edges) and the transition rates (edge labels). The graph yields a stochastic master equation for how microstate probabilities change over time. We show that this framework has broad scope by providing new insights into three very different ad hoc models, of steroid-hormone responsive genes, of inherently bounded chromatin domains and of the yeast PHO5 gene. We find, moreover, surprising complexity in the regulation of PHO5, which has not yet been experimentally explored, and we show that this complexity is an inherent feature of being away from equilibrium. At equilibrium, microstate probabilities do not depend on how a microstate is reached but, away from equilibrium, each path to a microstate can contribute to its steady-state probability. Systems that are far from equilibrium thereby become dependent on history and the resulting complexity is a fundamental challenge. To begin addressing this, we introduce a graph-based concept of independence, which can be applied to sub-systems that are far from equilibrium, and prove that history-dependent complexity can be circumvented when sub-systems operate independently.

CONCLUSIONS

As epigenomic data become increasingly available, we anticipate that gene function will come to be represented by graphs, as gene structure has been represented by sequences, and that the methods introduced here will provide a broader foundation for understanding how genes work.

Potency of progestogens used in hormonal therapy: toward understanding differential actions

Progestogens are widely used in contraception and in hormone therapy. Biochemical and molecular biological evidence suggests that progestogens differ widely in their affinities and transcriptional effects via different steroid receptors, and hence cannot be considered as a single class of compounds. Consistent with these observations, recent clinical evidence suggests that, despite their similar progestogenic actions, these differences underlie different side-effect profiles for cardiovascular disease and susceptibility to infectious diseases. However, choice of progestogen for maximal benefit and minimal side-effects is hampered by insufficient comparative clinical and molecular studies to understand their relative mechanisms of action, as well as their relative potencies for different assays and clinical effects. This review evaluates the usage, meaning and significance of the terms affinity, potency and efficacy in different models systems, with a view to improved understanding of their physiological and pharmacological significance. This article is part of a Special Issue entitled 'Menopause'.

Research resource: modulators of glucocorticoid receptor activity identified by a new high-throughput screening assay

Glucocorticoid steroids affect almost every type of tissue and thus are widely used to treat a variety of human pathological conditions. However, the severity of numerous side effects limits the frequency and duration of glucocorticoid treatments. Of the numerous approaches to control off-target responses to glucocorticoids, small molecules and pharmaceuticals offer several advantages. Here we describe a new, extended high-throughput screen in intact cells to identify small molecule modulators of dexamethasone-induced glucocorticoid receptor (GR) transcriptional activity. The novelty of this assay is that it monitors changes in both GR maximal activity (A(max)) and EC(50) (the position of the dexamethasone dose-response curve). Upon screening 1280 chemicals, 10 with the greatest changes in the absolute value of A(max) or EC(50) were selected for further examination. Qualitatively identical behaviors for 60% to 90% of the chemicals were observed in a completely different system, suggesting that other systems will be similarly affected by these chemicals. Additional analysis of the 10 chemicals in a recently described competition assay determined their kinetically defined mechanism and site of action. Some chemicals had similar mechanisms of action despite divergent effects on the level of the GR-induced product. These combined assays offer a straightforward method of identifying numerous new pharmaceuticals that can alter GR transactivation in ways that could be clinically useful.

A kinase-independent activity of Cdk9 modulates glucocorticoid receptor-mediated gene induction

A gene induction competition assay has recently uncovered new inhibitory activities of two transcriptional cofactors, NELF-A and NELF-B, in glucocorticoid-regulated transactivation. NELF-A and -B are also components of the NELF complex, which participates in RNA polymerase II pausing shortly after the initiation of gene transcription. We therefore asked if cofactors (Cdk9 and ELL) best known to affect paused polymerase could reverse the effects of NELF-A and -B. Unexpectedly, Cdk9 and ELL augmented, rather than prevented, the effects of NELF-A and -B. Furthermore, Cdk9 actions are not blocked either by Ckd9 inhibitors (DRB or flavopiridol) or by two Cdk9 mutants defective in kinase activity. The mode and site of action of NELF-A and -B mutants with an altered NELF domain are similarly affected by wild-type and kinase-dead Cdk9. We conclude that Cdk9 is a new modulator of GR action, that Ckd9 and ELL have novel activities in GR-regulated gene expression, that NELF-A and -B can act separately from the NELF complex, and that Cdk9 possesses activities that are independent of Cdk9 kinase activity. Finally, the competition assay has succeeded in ordering the site of action of several cofactors of GR transactivation. Extension of this methodology should be helpful in determining the site and mode of action of numerous additional cofactors and in reducing unwanted side effects.

Minireview: dynamic structures of nuclear hormone receptors: new promises and challenges

Therapeutic targeting of nuclear receptors (NRs) is presently restricted due to 2 constraints: 1) a limited knowledge of the structural dynamics of intact receptor when complexed to DNA and coregulatory proteins; and 2) the inability to more selectively modulate NR actions at specific organ/gene targets. A major obstacle has been the current lack of understanding about the function and structure of the intrinsically disordered N-terminal domain that contains a major regulatory transcriptional activation function (AF1). Current studies of both mechanism of action and small molecule-selective receptor modulators for clinical uses target the structured pocket of the ligand-binding domain to modulate coregulatory protein interactions with the other activation function AF2. However, these approaches overlook AF1 activity. Recent studies have shown that highly flexible intrinsically disordered regions of transcription factors, including that of the N-terminal domain AF1 of NRs, not only are critical for several aspects of NR action but also can be exploited as drug targets, thereby opening unique opportunities for endocrine-based therapies. In this review article, we discuss the role of structural flexibilities in the allosteric modulation of NR activity and future perspectives for therapeutic interventions.

A conserved protein motif is required for full modulatory activity of negative elongation factor subunits NELF-A and NELF-B in modifying glucocorticoid receptor-regulated gene induction properties

NELF-B is a BRCA1-interacting protein and subunit (with NELF-A, -C/D, and -E) of the human negative elongation factor (NELF) complex, which participates in RNA polymerase II pausing shortly after transcription initiation, especially for synchronized gene expression. We now report new activities of NELF-B and other NELF complex subunits, which are to attenuate glucocorticoid receptor (GR)-mediated gene induction, reduce the partial agonist activity of an antagonist, and increase the EC50 of an agonist during nonsynchronized expression of exogenous and endogenous reporters. Stable knockdown of endogenous NELF-B has the opposite effects on an exogenous gene. The GR ligand-binding domain suffices for these biological responses. ChIP assays reveal that NELF-B diminishes GR recruitment to promoter regions of two endogenous genes. Using a new competition assay, NELF-A and NELF-B are each shown to act independently as competitive decelerators at two steps after the site of GR action and before or at the site of reporter gene activity. A common motif in each NELF was identified that is required for full activity of both NELF-A and NELF-B. These studies allow us to position the actions of two new modulators of GR-regulated transactivation, NELF-A and NELF-B, relative to other factors in the overall gene induction sequence.

Direct observation of frequency modulated transcription in single cells using light activation

Single-cell analysis has revealed that transcription is dynamic and stochastic, but tools are lacking that can determine the mechanism operating at a single gene. Here we utilize single-molecule observations of RNA in fixed and living cells to develop a single-cell model of steroid-receptor mediated gene activation. We determine that steroids drive mRNA synthesis by frequency modulation of transcription. This digital behavior in single cells gives rise to the well-known analog dose response across the population. To test this model, we developed a light-activation technology to turn on a single steroid-responsive gene and follow dynamic synthesis of RNA from the activated locus.

DOI:http://dx.doi.org/10.7554/eLife.00750.001

The process by which a gene is expressed as a protein consists of two stages: transcription, which involves the DNA of the gene being copied into messenger RNA (mRNA); and translation, in which the mRNA is used as a template to assemble amino acids into a protein. Transcription and translation are controlled by many interlinked pathways, which ensures that genes are expressed when and where required.

One of these regulatory pathways involves steroid receptors. The binding of a steroid molecule to its receptor causes the receptor to move into the nucleus and interact with a specific gene, triggering transcription of that gene. When measured at the level of the whole organism, this transcriptional response is dose-dependent—the more steroid molecules that are present, the greater the amount of transcription. However, this is not the case in single cells, in which transcription is either activated or not. This ‘on/off’ behaviour is also seen over time: steroid-activated transcription occurs in bursts, separated by periods of inactivity.

To unravel the molecular mechanism behind this phenomenon, Larson et al. created a light-activated form of the ligand that activates a specific steroid receptor. Using this molecule, they were able to switch transcription of the gene controlled by that receptor on and off. They then used fluorescent proteins to label the mRNA and protein molecules that were produced as a result.

They found that activating the steroid receptor increases the likelihood of transcription occurring inside a cell, but not the duration of individual bursts of transcriptional activity, nor the amount of mRNA produced during each burst. Activation of a steroid receptor seems to control transcription by reducing the length of time each cell spends in the ‘off’ state between bursts.

Larson et al. incorporated their findings into a model that also takes into account the natural variability in levels of transcription between cells, and found that this could explain how the digital (on/off) control of transcription at the cellular level leads to analogue, dose-dependent control at the level of a whole organism. These findings should lead to further insights into how transcription is controlled at the molecular level.

DOI:http://dx.doi.org/10.7554/eLife.00750.002

Variable steroid receptor responses: Intrinsically disordered AF1 is the key

Steroid hormones, acting through their cognate receptor proteins, see widespread clinical applications due to their ability to alter the induction or repression of numerous genes. However, steroid usage is limited by the current inability to control off-target, or non-specific, side-effects. Recent results from three separate areas of research with glucocorticoid and other steroid receptors (cofactor-induced changes in receptor structure, the ability of ligands to alter remote regions of receptor structure, and how cofactor concentration affects both ligand potency and efficacy) indicate that a key element of receptor activity is the intrinsically disordered amino-terminal domain. These results are combined to construct a novel framework within which to logically pursue various approaches that could afford increased selectivity in steroid-based therapies.

Eukaryotic transcriptional dynamics: from single molecules to cell populations

Transcriptional regulation is achieved through combinatorial interactions between regulatory elements in the human genome and a vast range of factors that modulate the recruitment and activity of RNA polymerase. Experimental approaches for studying transcription in vivo now extend from single-molecule techniques to genome-wide measurements. Parallel to these developments is the need for testable quantitative and predictive models for understanding gene regulation. These conceptual models must also provide insight into the dynamics of transcription and the variability that is observed at the single-cell level. In this Review, we discuss recent results on transcriptional regulation and also the models those results engender. We show how a non-equilibrium description informs our view of transcription by explicitly considering time- and energy-dependence at the molecular level.

Impact of glucocorticoid receptor density on ligand-independent dimerization, cooperative ligand-binding and basal priming of transactivation: a cell culture model

Glucocorticoid receptor (GR) levels vary between tissues and individuals and are altered by physiological and pharmacological effectors. However, the effects and implications of differences in GR concentration have not been fully elucidated. Using three statistically different GR concentrations in transiently transfected COS-1 cells, we demonstrate, using co-immunoprecipitation (CoIP) and fluorescent resonance energy transfer (FRET), that high levels of wild type GR (wtGR), but not of dimerization deficient GR (GRdim), display ligand-independent dimerization. Whole-cell saturation ligand-binding experiments furthermore establish that positive cooperative ligand-binding, with a concomitant increased ligand-binding affinity, is facilitated by ligand-independent dimerization at high concentrations of wtGR, but not GRdim. The down-stream consequences of ligand-independent dimerization at high concentrations of wtGR, but not GRdim, are shown to include basal priming of the system as witnessed by ligand-independent transactivation of both a GRE-containing promoter-reporter and the endogenous glucocorticoid (GC)-responsive gene, GILZ, as well as ligand-independent loading of GR onto the GILZ promoter. Pursuant to the basal priming of the system, addition of ligand results in a significantly greater modulation of transactivation potency than would be expected solely from the increase in ligand-binding affinity. Thus ligand-independent dimerization of the GR at high concentrations primes the system, through ligand-independent DNA loading and transactivation, which together with positive cooperative ligand-binding increases the potency of GR agonists and shifts the bio-character of partial GR agonists. Clearly GR-levels are a major factor in determining the sensitivity to GCs and a critical factor regulating transcriptional programs.

Use and validation of HT/HC assays to support 21st century toxicity evaluations

Advances in high throughput and high content (HT/HC) methods such as those used in the fields of toxicogenomics, bioinformatics, and computational toxicology have the potential to improve both the efficiency and effectiveness of toxicity evaluations and risk assessments. However, prior to use, scientific confidence in these methods should be formally established. Traditional validation approaches that define relevance, reliability, sensitivity and specificity may not be readily applicable. HT/HC methods are not exact replacements for in vivo testing, and although run individually, these assays are likely to be used as a group or battery for decision making and use robotics, which may be unique in each laboratory setting. Building on the frameworks developed in the 2010 Institute of Medicine Report on Biomarkers and the OECD 2007 Report on (Q)SAR Validation, we present constructs that can be adapted to address the validation challenges of HT/HC methods. These are flexible, transparent, and require explicit specification of context and purpose of use such that scientific confidence (validation) can be defined to meet different regulatory applications. Using these constructs, we discuss how anchoring the assays and their prediction models to Adverse Outcome Pathways (AOPs) could facilitate the interpretation of results and support scientifically defensible fit-for-purpose applications.

PA1 protein, a new competitive decelerator acting at more than one step to impede glucocorticoid receptor-mediated transactivation

Numerous cofactors modulate the gene regulatory activity of glucocorticoid receptors (GRs) by affecting one or more of the following three major transcriptional properties: the maximal activity of agonists (A(max)), the potency of agonists (EC(50)), and the partial agonist activity of antisteroids (PAA). Here, we report that the recently described nuclear protein, Pax2 transactivation domain interaction protein (PTIP)-associated protein 1 (PA1), is a new inhibitor of GR transactivation. PA1 suppresses A(max), increases the EC(50), and reduces the PAA of an exogenous reporter gene in a manner that is independent of associated PTIP. PA1 is fully active with, and strongly binds to, the C-terminal half of GR. PA1 reverses the effects of the coactivator TIF2 on GR-mediated gene induction but is unable to augment the actions of the corepressor SMRT. Analysis of competition assays between PA1 and TIF2 with an exogenous reporter indicates that the kinetic definition of PA1 action is a competitive decelerator at two sites upstream from where TIF2 acts. With the endogenous genes IGFBP1 and IP6K3, PA1 also represses GR induction, increases the EC(50), and decreases the PAA. ChIP and re-ChIP experiments indicate that PA1 accomplishes this inhibition of the two genes via different mechanisms as follows: PA1 appears to increase GR dissociation from and reduce GR transactivation at the IGFBP1 promoter regions but blocks GR binding to the IP6K3 promoter. We conclude that PA1 is a new competitive decelerator of GR transactivation and can act at more than one molecularly defined step in a manner that depends upon the specific gene.

Identification of location and kinetically defined mechanism of cofactors and reporter genes in the cascade of steroid-regulated transactivation

A currently obscure area of steroid hormone action is where the component factors, including receptor and reporter gene, act. The DNA binding of factors can be precisely defined, but the location and timing of factor binding and action are usually not equivalent. These questions are addressed for several factors (e.g. glucocorticoid receptor (GR), reporter, TIF2, NCoR, NELF-A, sSMRT, and STAMP) using our recently developed competition assay. This assay reveals both the kinetically defined mechanism of factor action and where the above factors act relative to both each other and the equilibrium equivalent to the rate-limiting step, which we call the concentration limiting step (CLS). The utility of this competition assay would be greatly increased if the position of the CLS is invariant and if the factor acting at the CLS is known. Here we report that the exogenous GREtkLUC reporter acts at the CLS as an accelerator for gene induction by GRs in U2OS cells. This mechanism of reporter function at the CLS persists with different reporters, factors, receptors, and cell types. We, therefore, propose that the reporter gene always acts at the CLS during gene induction and constitutes a landmark around which one can order the actions of all other factors. Current data suggest that how and where GR and the short form of SMRT act is also constant. These results validate a novel and rational methodology for identifying distally acting factors that would be attractive targets for pharmaceutical intervention in the treatment of diseases involving GR-regulated genes.

The hypersensitive glucocorticoid response specifically regulates period 1 and expression of circadian genes

Glucocorticoids regulate gene expression by binding and activating the glucocorticoid receptor (GR). While ligand affinity determines the global sensitivity of the response, additional proteins act on the genome to tune sensitivity of some genes. However, the genomic extent and specificity of dose-specific glucocorticoid responses are unknown. We show that dose-specific glucocorticoid responses are extraordinarily specific at the genomic scale, able to distinctly express a single gene, the circadian rhythm gene for Period 1 (PER1), at concentrations consistent with the nighttime nadir of human cortisol. We mapped the PER1 response to a single GR binding site. The specific GR binding sequence did not impact sensitivity, and we instead attributed the response to a combination of additional transcription factors and chromatin accessibility acting in the same locus. The PER1 hypersensitive response element is conserved in the mouse, where we found similar upregulation of Per1 in pituitary cells. Targeted and transient overexpression of PER1 led to regulation of additional circadian rhythm genes hours later, suggesting that hypersensitive expression of PER1 impacts circadian gene expression. These findings show that hypersensitive GR binding occurs throughout the genome, drives targeted gene expression, and may be important to endocrine mediation of peripheral circadian rhythms.

Quantitative analysis of the bidirectional viral G-protein-coupled receptor and lytic latency-associated nuclear antigen promoter of Kaposi's sarcoma-associated herpesvirus

Kaposi's sarcoma-associated herpesvirus (KSHV) establishes sustained latent persistence in susceptible cells. This is dependent on the latency-associated nuclear antigen (LANA). Understanding how LANA transcription is regulated thus aids our fundamental understanding of KSHV biology. Two hundred ninety-four base pairs are sufficient to regulate LANA transcription in response to the viral RTA protein and RBPjκ. The same region controls K14/viral G-protein-coupled receptor (vGPCR) transcription in the opposite direction. We used a quantitative analysis in conjunction with specific nucleotide substitutions and defined gain-of-function and loss-of-function RTA mutants to dissect this region. We used a bidirectional reporter driving red and green luciferase to study the LANApi and K14p promoters simultaneously. This established that LANApi/K14p functions as a canonical bidirectional promoter. Both were TATA dependent. K14p was favored by ∼50-fold in this context. Eliminating the distal LANApi TATA box increased maximal output and lowered the induction threshold (T) of K14p even further. Two RBPjκ binding sites were independently required; however, at high concentrations of RTA, direct interactions with an RTA-responsive element (RRE) could complement the loss of one RBPjκ binding site. Intracellular Notch (ICN) was no longer able to activate RBPjκ in the viral context. This suggests a model whereby KSHV alters ICN-RBPjκ gene regulation. When the architecture of this pair of head-to-head RBPjκ binding sites is changed, the sites now respond exclusively to the viral transactivator RTA and no longer to the host mediator ICN.

Glucocorticoid receptor-DNA interactions: binding energetics are the primary determinant of sequence-specific transcriptional activity

The glucocorticoid receptor (GR) is a member of the steroid receptor family of ligand-activated transcription factors. A long-standing question has focused on how GR and other receptors precisely control gene expression. One difficulty in addressing this is that GR function is influenced by multiple factors including ligand and coactivator levels, chromatin state, and allosteric coupling. Moreover, the receptor recognizes an array of DNA sequences that generate a range of transcriptional activities. Such complexity suggests that any single parameter-DNA binding affinity, for example-is unlikely to be a dominant contributor to function. Indeed, a number of studies have suggested that for GR and other receptors, binding affinity toward different DNA sequences is poorly correlated with transcriptional activity. As a step toward determining the factors most predictive of GR function, we rigorously examined the relationship between in vitro GR-DNA binding energetics and in vivo transcriptional activity. We first demonstrate that previous approaches for assessing affinity-function relationships are problematic due to issues of data transformation and linearization. Thus, the conclusion that binding energetics and transcriptional activity are poorly correlated is premature. Using more appropriate analyses, we find that energetics and activity are in fact highly correlated. Furthermore, this correlation can be quantitatively accounted for using simple binding models. Finally, we show that the strong relationship between energetics and transcriptional activity is recapitulated in multiple promoter contexts, cell lines, and chromatin environments. Thus, despite the complexity of GR function, DNA binding energetics are the primary determinant of sequence-specific transcriptional activity.

Separate regions of glucocorticoid receptor, coactivator TIF2, and comodulator STAMP modify different parameters of glucocorticoid-mediated gene induction

Increased specificity in steroid-regulated gene expression is a long-sought goal of endocrinologists. Considerable progress has resulted from the discovery of coactivators, corepressors, and comodulators that adjust the total activity (A(max)) of gene induction. Two less frequently quantitated, but equally potent, means of improving specificity are the concentration of agonist steroid required for half-maximal activity (EC(50)) and the residual or partial agonist activity displayed by most antisteroids (PAA). It is usually assumed that the modulatory activity of transcriptional cofactors coordinately regulates A(max), EC(50), and PAA. Here we examine the hypothesis that these three parameters can be independently modified by separate protein domains. The test system involves three differently sized fragments of each of three factors (glucocorticoid receptor [GR], coactivator TIF2, and comodulator STAMP), which are shown to form a ternary complex and similarly affect the induction properties of transfected and endogenous genes. Twenty-five different fragment combinations of the ternary complex are examined for their ability to modulate the A(max), EC(50), and PAA of a transiently transfected synthetic reporter gene. Different combinations selectively alter one, two, or all three parameters. These results clearly demonstrate that A(max), EC(50), and PAA can be independently regulated under some conditions by different pathways or molecular interactions. This new mechanistic insight suggests that selected activities of individual transcription factors are attractive targets for small molecules, which would have obvious clinical applications for increasing the specificity of steroids during endocrine therapies.

Mapping gene-environment interactions at regulatory polymorphisms: insights into mechanisms of phenotypic variation

Genetic effects on gene regulation make a substantial contribution to phenotypic diversity, yet their mechanisms remain elusive. Here, we discuss the potential insights to be gained from mapping gene-environment interactions at regulatory polymorphisms (i.e., genetic variation that affects gene expression under specific environmental conditions). We highlight a novel statistical method to identify specific patterns of gene-environment interaction at these regulatory polymorphisms. Reviewing its application to a study that mapped gene expression in the presence and absence of glucocorticoids, we discuss the mechanistic insights that this approach provides.

The road less traveled: new views of steroid receptor action from the path of dose-response curves

Conventional studies of steroid hormone action proceed via quantitation of the maximal activity for gene induction at saturating concentrations of agonist steroid (i.e., A(max)). Less frequently analyzed parameters of receptor-mediated gene expression are EC(50) and PAA. The EC(50) is the concentration of steroid required for half-maximal agonist activity and is readily determined from the dose-response curve. The PAA is the partial agonist activity of an antagonist steroid, expressed as percent of A(max) under the same conditions. Recent results demonstrate that new and otherwise inaccessible mechanistic information is obtained when the EC(50) and/or PAA are examined in addition to the A(max). Specifically, A(max), EC(50), and PAA can be independently regulated, which suggests that novel pathways and factors may preferentially modify the EC(50) and/or PAA with little effect on A(max). Other approaches indicate that the activity of receptor-bound factors can be altered without changing the binding of factors to receptor. Finally, a new theoretical model of steroid hormone action not only permits a mechanistically based definition of factor activity but also allows the positioning of when a factor acts, as opposed to binds, relative to a kinetically defined step. These advances illustrate some of the benefits of expanding the mechanistic studies of steroid hormone action to routinely include EC(50) and PAA.

Deducing the temporal order of cofactor function in ligand-regulated gene transcription: theory and experimental verification

Cofactors are intimately involved in steroid-regulated gene expression. Two critical questions are (1) the steps at which cofactors exert their biological activities and (2) the nature of that activity. Here we show that a new mathematical theory of steroid hormone action can be used to deduce the kinetic properties and reaction sequence position for the functioning of any two cofactors relative to a concentration limiting step (CLS) and to each other. The predictions of the theory, which can be applied using graphical methods similar to those of enzyme kinetics, are validated by obtaining internally consistent data for pair-wise analyses of three cofactors (TIF2, sSMRT, and NCoR) in U2OS cells. The analysis of TIF2 and sSMRT actions on GR-induction of an endogenous gene gave results identical to those with an exogenous reporter. Thus new tools to determine previously unobtainable information about the nature and position of cofactor action in any process displaying first-order Hill plot kinetics are now available.

What do expression dynamics tell us about the mechanism of transcription?

Single-cell microscopy studies have the potential to provide an unprecedented view of gene expression with exquisite spatial and temporal sensitivity. However, there is a challenge to connect the holistic cellular view with a reductionist biochemical view. In particular, experimental efforts to characterize the in vivo regulation of transcription have focused primarily on measurements of the dynamics of transcription factors and chromatin modifying factors. Such measurements have elucidated the transient nature of many nuclear interactions. In the past few years, experimental approaches have emerged that allow for interrogation of the output of transcription at the single-molecule, single-cell level. Here, I summarize the experimental results and models that aim to provide an integrated view of transcriptional regulation.

Corticosteroid receptor signalling modes and stress adaptation in the brain

Adrenal glucocorticoid hormones modulate neuronal activity to support an adaptive response to stress. They modulate brain circuitry mediating physiological responses, emotion and cognitive processing. Chronically elevated glucocorticoid exposure is however linked to the development of mental disease. Glucocorticoid effects depend on mineralo- and glucocorticoid receptors, which are powerful transcription factors, but also can act via a diversity of non-genomic mechanisms. Here, I review generic factors that determine neuronal glucocorticoid sensitivity, in relation to brain function. First, pre-receptor mechanisms determine ligand availability. Second, there may be considerable variation in the receptor splice- and translation variants. Third, other transcription factors and many transcriptional coregulators interact with steroid receptors, determining nature and magnitude of steroid responses, in part through epigenetic regulation of DNA accessibility. Which factors underlie adaptive and pathogenic effects of stress hormones is largely unknown. Genome-wide identification of the receptor-DNA interactions in specific behavioural and physiological contexts provides a way of assessing the complete genomic range of glucocorticoid modes of action. Novel ligands that induce selective activation of particular receptor signalling modes will aid our understanding of receptor signalling and may allow selective targeting of glucocorticoid effects in emotional or cognitive domains, in research and, hopefully, in clinical settings.

Inferring mechanisms from dose-response curves

The steady state dose-response curve of ligand-mediated gene induction usually appears to precisely follow a first-order Hill equation (Hill coefficient equal to 1). Additionally, various cofactors/reagents can affect both the potency and the maximum activity of gene induction in a gene-specific manner. Recently, we have developed a general theory for which an unspecified sequence of steps or reactions yields a first-order Hill dose-response curve (FHDC) for plots of the final product versus initial agonist concentration. The theory requires only that individual reactions "dissociate" from the downstream reactions leading to the final product, which implies that intermediate complexes are weakly bound or exist only transiently. We show how the theory can be utilized to make predictions of previously unidentified mechanisms and the site of action of cofactors/reagents. The theory is general and can be applied to any biochemical reaction that has a FHDC.

Ligand binding domain mutations of the glucocorticoid receptor selectively modify the effects with, but not binding of, cofactors

We previously reported that several point mutations in the ligand binding domain (LBD) of glucocorticoid receptors (GRs) marginally affect the binding affinity of the synthetic glucocorticoids dexamethasone (Dex) and deacylcortivazol (DAC). However, these mutations dramatically alter the efficacy (A(max)) and potency (EC(50)) of agonists, along with the partial agonist activity (PAA) of the antisteroid Dex-mesylate (DM), for gene induction and repression in a steroid-dependent manner. This was proposed to result, in part, from altered protein-protein interactions in the complex of GR with the coactivator TIF2 despite normal TIF2 binding. To explore the generality of this phenomenon, we now ask whether these mutations also affect the transactivation properties, but not binding, of other GR-bound factors. We find that an elevated concentration of GR, to probe unidentified cofactors, or of the comodulator Ubc9 does not reverse the effects of GR LBD mutations that increase the EC(50) and lower the PAA with the GREtkLUC reporter in both CV-1 and U2OS cells. This behavior is more dramatic with Ubc9 and the isolated GR LBD fused to the GAL4 DNA binding domain, despite normal binding of Ubc9 to the mutant GRs. Similar effects, albeit gene, steroid, and transcriptional property-specific, are seen with full-length GRs and three endogenous genes in U2OS cells. Thus, changes in simple steady-state binding capacities of mutant receptors for factors cannot account for the modified transcriptional properties. In all cases, the nuclear translocation of Dex- and DAC-bound wild-type and mutant receptors is the same. These results are consistent with the earlier results with TIF2 and support the hypothesis that small changes in the GR LBD can alter the activities of the bound cofactor without modifying cofactor binding. We propose that this separation of binding and the modulation of transactivation parameters occurs for a wide variety of GR-associated cofactors.

Glucocorticoid receptor cofactors as therapeutic targets

Numerous transcriptional cofactors (e.g. coactivators, corepressors, and comodulators) are known to alter the maximal transcriptional activity (A(max)) in gene induction and repression by steroid receptors in general and glucocorticoid receptors (GRs) in particular. However, recent data advance the earlier reports that these same factors also modify other parameters of glucocorticoid receptor transcriptional activity: the potency of agonists (or EC₅₀ and the partial agonist activity of antisteroids (or PAA). In several instances, factors modulate the EC₅₀ and/or PAA without changing A(max). Thus, studies of all three parameters reveal new factors acting at various stages of receptor action, thereby increasing the potential therapeutic targets for adjusting GR actions in pathological situations.