Mechanism of Transcription Factor Recruitment by Acidic Activators
2005; Elsevier BV; Volume: 280; Issue: 23 Linguagem: Inglês
10.1074/jbc.m502627200
ISSN1083-351X
AutoresMonica E. Ferreira, Stefan Hermann, Philippe Prochasson, Jerry L. Workman, Kurt D. Berndt, Anthony P. H. Wright,
Tópico(s)RNA and protein synthesis mechanisms
ResumoMany transcriptional activators are intrinsically unstructured yet display unique, defined conformations when bound to target proteins. Target-induced folding provides a mechanism by which activators could form specific interactions with an array of structurally unrelated target proteins. Evidence for such a binding mechanism has been reported previously in the context of the interaction between the cancer-related c-Myc protein and the TATA-binding protein, which can be modeled as a two-step process in which a rapidly forming, low affinity complex slowly converts to a more stable form, consistent with a coupled binding and folding reaction. To test the generality of the target-induced folding model, we investigated the binding of two widely studied acidic activators, Gal4 and VP16, to a set of target proteins, including TATA-binding protein and the Swi1 and Snf5 subunits of the Swi/Snf chromatin remodeling complex. Using surface plasmon resonance, we show that these activator-target combinations also display bi-phasic kinetics suggesting two distinct steps. A fast initial binding phase that is inhibited by high ionic strength is followed by a slow phase that is favored by increased temperature. In all cases, overall affinity increases with temperature and, in most cases, with increased ionic strength. These results are consistent with a general mechanism for recruitment of transcriptional components to promoters by naturally occurring acidic activators, by which the initial contact is mediated predominantly through electrostatic interactions, whereas subsequent target-induced folding of the activator results in a stable complex. Many transcriptional activators are intrinsically unstructured yet display unique, defined conformations when bound to target proteins. Target-induced folding provides a mechanism by which activators could form specific interactions with an array of structurally unrelated target proteins. Evidence for such a binding mechanism has been reported previously in the context of the interaction between the cancer-related c-Myc protein and the TATA-binding protein, which can be modeled as a two-step process in which a rapidly forming, low affinity complex slowly converts to a more stable form, consistent with a coupled binding and folding reaction. To test the generality of the target-induced folding model, we investigated the binding of two widely studied acidic activators, Gal4 and VP16, to a set of target proteins, including TATA-binding protein and the Swi1 and Snf5 subunits of the Swi/Snf chromatin remodeling complex. Using surface plasmon resonance, we show that these activator-target combinations also display bi-phasic kinetics suggesting two distinct steps. A fast initial binding phase that is inhibited by high ionic strength is followed by a slow phase that is favored by increased temperature. In all cases, overall affinity increases with temperature and, in most cases, with increased ionic strength. These results are consistent with a general mechanism for recruitment of transcriptional components to promoters by naturally occurring acidic activators, by which the initial contact is mediated predominantly through electrostatic interactions, whereas subsequent target-induced folding of the activator results in a stable complex. Transcriptional activators function by binding specific DNA sequences in the promoter regions of target genes and subsequently recruiting components of the transcriptional machinery via their activation domains (ADs). 1The abbreviations used are: AD, activation domain; ABD, activator binding domain; TBP, TATA-box binding protein; GST, glutathione S-transferase; SPR, surface plasmon resonance; RU, resonance unit(s). Activation domains have to be able to interact with multiple structurally unrelated target proteins because eukaryotic genes require successive recruitment of different co-activator proteins (1Cosma M.P. Tanaka T. Nasmyth K. Cell. 1999; 97: 299-311Abstract Full Text Full Text PDF PubMed Scopus (604) Google Scholar), and different target genes utilize different repertoires of co-activators, even if they are regulated by the same activator (2Gregory P.D. Schmid A. Zavari M. Munsterkotter M. Horz W. EMBO J. 1999; 18: 6407-6414Crossref PubMed Scopus (119) Google Scholar, 3Gregory P.D. Schmid A. Zavari M. Lui L. Berger S.L. Horz W. Mol. Cell. 1998; 1: 495-505Abstract Full Text Full Text PDF PubMed Scopus (109) Google Scholar). The mechanism by which activator proteins make specific interactions with structurally distinct target proteins is, however, poorly understood. Many activation domains are known to be intrinsically unstructured but are found in a folded conformation when bound to target proteins (for review, see Ref. 4Dyson H.J. Wright P.E. Curr. Opin. Struct. Biol. 2002; 12: 54-60Crossref PubMed Scopus (1132) Google Scholar). Whereas the structures of the initial and final states of some systems have been characterized, the determinants of complementarity, as well as the mechanism of the coupled folding and binding event, remain unknown. Support for the physiological significance of this transition has been provided by studies showing the unstructured nature of activation domains, even in the context of intact activator proteins (5Grossmann J.G. Sharff A.J. O'Hare P. Luisi B. Biochemistry. 2001; 40: 6267-6274Crossref PubMed Scopus (32) Google Scholar, 6Ayed A. Mulder F.A.A. Yi G.S. Lu Y. Kay L.E. Arrowsmith C.H. Nat. Struct. Biol. 2001; 8: 756-760Crossref PubMed Scopus (236) Google Scholar). In addition, mutations, causing substitutions of hydrophobic residues that might be expected to affect folding of the glucocorticoid receptor tau1 activation domain have been shown to cause changes in the activity of the intact receptor protein (7Almlöf T. Gustafsson J Å. Wright A.P.H. Mol. Cell. Biol. 1997; 17: 934-945Crossref PubMed Scopus (63) Google Scholar). We have previously reported that the activation domain from the cancer-related c-Myc protein interacts with the TATA-binding protein (TBP) in two steps, such that folding of the c-Myc activation domain is coupled to its interaction with the surface of TBP (8Hermann S. Berndt K.D. Wright A.P. J. Biol. Chem. 2001; 276: 40127-40132Abstract Full Text Full Text PDF PubMed Scopus (40) Google Scholar). Coupled binding and folding could explain how activators are able to interact specifically with a large set of structurally different targets in the transcriptional machinery and recruit them to promoters. The c-Myc activation domain is unusual because it is divided in two protein segments that are interspersed with sequences that destabilize c-Myc by targeting its proteasome-mediated degradation (9Flinn E.M. Busch C.M. Wright A.P. Mol. Cell. Biol. 1998; 18: 5961-5969Crossref PubMed Scopus (104) Google Scholar, 10Flinn E.M. Wallberg A.E. Hermann S. Grant P.A. Workman J.L. Wright A.P. J. Biol. Chem. 2002; 277: 23399-23406Abstract Full Text Full Text PDF PubMed Scopus (27) Google Scholar). Unlike the c-Myc activation domain, many activation domains consist of short protein segments that are rich in acidic amino acids. Two examples of acidic transcriptional activators that display extensive structural flexibility in their activation domains are Gal4 and VP16 (5Grossmann J.G. Sharff A.J. O'Hare P. Luisi B. Biochemistry. 2001; 40: 6267-6274Crossref PubMed Scopus (32) Google Scholar, 11Leuther K.K. Salmeron J.M. Johnston S.A. Cell. 1993; 72: 575-585Abstract Full Text PDF PubMed Scopus (105) Google Scholar, 12Uesugi M. Nyanguile O. Lu H. Levine A.J. Verdine G.L. Science. 1997; 277: 1310-1313Crossref PubMed Scopus (273) Google Scholar). Gal4 regulates the genes required for galactose metabolism in yeast (13Johnston M. Microbiol. Rev. 1987; 51: 458-476Crossref PubMed Google Scholar). The C-terminal activation domain of Gal4 also contains the interaction site for Gal80, which inhibits Gal4 activity under non-inducing conditions (14Ma J. Ptashne M. Cell. 1987; 48: 847-853Abstract Full Text PDF PubMed Scopus (604) Google Scholar, 15Ma J. Ptashne M. Cell. 1987; 50: 137-142Abstract Full Text PDF PubMed Scopus (218) Google Scholar, 16Johnston M. Flick J.S. Pexton T. Mol. Cell. Biol. 1994; 14: 3834-3841Crossref PubMed Scopus (200) Google Scholar, 17Rohde J.R. Trinh J. Sadowski I. Mol. Cell. Biol. 2000; 20: 3880-3886Crossref PubMed Scopus (57) Google Scholar). VP16 is a co-activator involved in activation of immediate early viral genes in herpes simplex-infected cells, and the C-terminal domain has been identified as an activation domain (18Triezenberg S.J. Kingsbury R.C. Mcknight S.L. Genes Dev. 1988; 2: 718-729Crossref PubMed Scopus (596) Google Scholar, 19Preston C.M. Frame M.C. Campbell M.E.M. Cell. 1988; 52: 425-434Abstract Full Text PDF PubMed Scopus (218) Google Scholar). Acidic activators have been proposed to interact with target proteins by complementary electrostatic interactions mediated via their acidic residues, without adopting defined structures (20Sigler P.B. Nature. 1988; 333: 210-212Crossref PubMed Scopus (300) Google Scholar, 21Ansari A.Z. Reece R.J. Ptashne M. Proc. Natl. Acad. Sci. U. S. A. 1998; 95: 13543-13548Crossref PubMed Scopus (48) Google Scholar). However, it has also been demonstrated that critical hydrophobic amino acids are essential for both target factor binding and the activating potential of acidic activation domains, whereas mutating individual acidic residues has little or no effect (7Almlöf T. Gustafsson J Å. Wright A.P.H. Mol. Cell. Biol. 1997; 17: 934-945Crossref PubMed Scopus (63) Google Scholar, 11Leuther K.K. Salmeron J.M. Johnston S.A. Cell. 1993; 72: 575-585Abstract Full Text PDF PubMed Scopus (105) Google Scholar, 22Almlöf T. Wright A.P.H. Gustafsson J. Å. J. Biol. Chem. 1995; 270: 17535-17540Abstract Full Text Full Text PDF PubMed Scopus (89) Google Scholar, 23Cress W.D. Triezenberg S.J. Science. 1991; 251: 87-90Crossref PubMed Scopus (324) Google Scholar, 24Lin J.Y. Chen J.D. Elenbaas B. Levine A.J. Genes Dev. 1994; 8: 1235-1246Crossref PubMed Scopus (581) Google Scholar, 25Regier J.L. Shen F. Triezenberg S.J. Proc. Natl. Acad. Sci. U. S. A. 1993; 90: 883-887Crossref PubMed Scopus (226) Google Scholar, 26Sullivan S.M. Horn P.J. Olson V.A. Koop A.H. Niu W. Ebright R.H. Triezenberg S.J. Nucleic Acids Res. 1998; 26: 4487-4496Crossref PubMed Scopus (57) Google Scholar). These results underscore the importance of critical hydrophobic residues in the target interaction that could be coupled to the conformational changes referred to earlier. Indeed, the Gal4 and Gcn4 acidic activation domains have been shown to adopt β-sheet conformation under acidic conditions in vitro, and mutational analysis indicates that this is a structural requirement for the activation function of Gal4 (11Leuther K.K. Salmeron J.M. Johnston S.A. Cell. 1993; 72: 575-585Abstract Full Text PDF PubMed Scopus (105) Google Scholar, 27Van Hoy M. Leuther K.K. Kodadek T. Johnston S.A. Cell. 1993; 72: 587-594Abstract Full Text PDF PubMed Scopus (121) Google Scholar). However, a relatively recent report indicates that whereas conformational changes may be important for interaction with Gal80, they may not be significant for either the activation activity of Gal4 or its interaction with TBP (21Ansari A.Z. Reece R.J. Ptashne M. Proc. Natl. Acad. Sci. U. S. A. 1998; 95: 13543-13548Crossref PubMed Scopus (48) Google Scholar). Both the Gal4 and VP16 activation domains interact with TBP with an affinity that correlates with their potency (26Sullivan S.M. Horn P.J. Olson V.A. Koop A.H. Niu W. Ebright R.H. Triezenberg S.J. Nucleic Acids Res. 1998; 26: 4487-4496Crossref PubMed Scopus (57) Google Scholar, 28Ingles C.J. Shales M. Cress W.D. Triezenberg S.J. Greenblatt J. Nature. 1991; 351: 588-590Crossref PubMed Scopus (227) Google Scholar, 29Stringer K.F. Ingles C.J. Greenblatt J. Nature. 1990; 345: 783-786Crossref PubMed Scopus (408) Google Scholar, 30Melcher K. Johnston S.A. Mol. Cell. Biol. 1995; 15: 2839-2848Crossref PubMed Scopus (146) Google Scholar, 31Nedialkov Y.A. Triezenberg S.J. Arch. Biochem. Biophys. 2004; 425: 77-86Crossref PubMed Scopus (15) Google Scholar). We have recently shown that they can also recruit the Swi/Snf chromatin remodeling complex to activated promoters via interactions with specific segments within the Swi1 and Snf5 subunits of the complex (32Neely K.E. Hassan A.H. Wallberg A.E. Steger D.J. Cairns B.R. Wright A.P.H. Workman J.L. Mol. Cell. 1999; 4: 649-655Abstract Full Text Full Text PDF PubMed Scopus (213) Google Scholar, 33Neely K.E. Hassan A.H. Brown C.E. Howe L. Workman J.L. Mol. Cell. Biol. 2002; 22: 1615-1625Crossref PubMed Scopus (146) Google Scholar, 34Prochasson P. Neely K.E. Hassan A.H. Li B. Workman J.L. Mol. Cell. 2003; 12: 983-990Abstract Full Text Full Text PDF PubMed Scopus (75) Google Scholar). These activator-interacting segments are not required for the overall integrity of the Swi/Snf complex, but when both are deleted, interaction with activators is severely reduced. This reduction correlates with a similar reduction in the activation potential of Gal4 in yeast strains containing the defective Swi/Snf complex (34Prochasson P. Neely K.E. Hassan A.H. Li B. Workman J.L. Mol. Cell. 2003; 12: 983-990Abstract Full Text Full Text PDF PubMed Scopus (75) Google Scholar). The mechanisms by which these segments of the Swi/Snf complex interact with activator proteins have not been studied. Here we investigate whether the target-induced folding model for the mechanism of activator-target protein interactions that we previously suggested in the context of the interaction between c-Myc and TBP could be a general mechanism for the interaction of acidic transcriptional activators with a broader group of target proteins. Using surface plasmon resonance (SPR), we have focused on binding of the two highly acidic natural activators Gal4 and VP16 to the yeast target proteins TBP, Swi1, and Snf5. The results demonstrate that the target-induced folding model is applicable to a broader range of activator-target protein interactions. Plasmids and Proteins—pRSET-Snf5, which encodes amino acids 1–334 of yeast Snf5 with an N-terminal His6 tag, has been described previously (34Prochasson P. Neely K.E. Hassan A.H. Li B. Workman J.L. Mol. Cell. 2003; 12: 983-990Abstract Full Text Full Text PDF PubMed Scopus (75) Google Scholar) (referred to hereafter as Snf5ABD). pRSET-Swi1 encodes amino acids 329–547 of yeast Swi1 with an N-terminal His6 tag and was constructed as described for pRSET-Snf5 (34Prochasson P. Neely K.E. Hassan A.H. Li B. Workman J.L. Mol. Cell. 2003; 12: 983-990Abstract Full Text Full Text PDF PubMed Scopus (75) Google Scholar) (Swi1ABD). pT7yD encodes full-length yeast TBP (35Hoopes B.C. Leblanc J.F. Hawley D.K. J. Biol. Chem. 1992; 267: 11539-11547Abstract Full Text PDF PubMed Google Scholar). pGST-VP16 encodes amino acids 413–490 of VP16 (VP16AD), deletion mutant pGST-VP16Δ456 additionally lacks residues 456–490 (VP16Δ456) (18Triezenberg S.J. Kingsbury R.C. Mcknight S.L. Genes Dev. 1988; 2: 718-729Crossref PubMed Scopus (596) Google Scholar), and pGST-Gal4 encodes amino acids 769–881 of Gal4 (Gal4AD) (32Neely K.E. Hassan A.H. Wallberg A.E. Steger D.J. Cairns B.R. Wright A.P.H. Workman J.L. Mol. Cell. 1999; 4: 649-655Abstract Full Text Full Text PDF PubMed Scopus (213) Google Scholar, 36Carrozza M.J. John S. Sil A.K. Hopper J.E. Workman J.L. J. Biol. Chem. 2002; 277: 24648-24652Abstract Full Text Full Text PDF PubMed Scopus (30) Google Scholar). Each construct has an N-terminal GST tag. All proteins in this study were produced by overexpression in Escherichia coli strain BL21/(DE3)pLys by induction with 1 mm isopropyl β-d-thiogalactopyranoside. His-tagged Snf5ABD and Swi1ABD were expressed from fresh transformants in SOC medium at 37 °C and 25 °C, respectively. Cell pellets were resuspended in 20 mm Tris, pH 7.4, and 500 mm NaCl, supplemented with Complete Protease Inhibitor Mixture (Roche Applied Science) and lysed by thawing and sonication. Lysates were cleared by DNase treatment and centrifugation, and the soluble fraction was purified by affinity chromatography using nickel-nitrilotriacetic acid-agarose (Qiagen). Up to 40 mm imidazole in resuspension buffer was used for washing, prior to elution with 500 mm imidazole. Swi1ABD was dialyzed (Sigma; molecular weight cutoff, 12,000) against TC100 buffer (20 mm Tris, pH 7.4, 100 mm KCl, 2 mm EDTA, 10 mm 2-mercaptoethanol, and 10% glycerol), and Snf5ABD was dialyzed against HBS (10 mm HEPES, pH 7.4, 150 mm NaCl, 3 mm EDTA, and 0.005% Tween 20). GST and GST fusion proteins of VP16AD and Gal4AD were expressed in LB medium at 37 °C. Cell pellets were resuspended in 100 mm Tris, pH 7.4, and 100 mm NaCl supplemented with Complete Protease Inhibitor Mixture. They were subsequently treated essentially as described above, except that the soluble fraction was purified by affinity chromatography using glutathione-agarose (Sigma). Resuspension buffer was used for washing, prior to elution with 20 mm glutathione in resuspension buffer. GST and GST fusion proteins were dialyzed against phosphate-buffered saline. Yeast TBP was purified and treated as described previously (8Hermann S. Berndt K.D. Wright A.P. J. Biol. Chem. 2001; 276: 40127-40132Abstract Full Text Full Text PDF PubMed Scopus (40) Google Scholar). All proteins were frozen immediately following purification and subsequently stored at –70 °C until use. Protein concentrations were determined using Coomassie Protein Assay Reagent (Pierce). All proteins were at least 90–95% pure as judged by SDS-PAGE. SPR Analysis—Kinetic experiments were performed on a BIA-core2000 instrument under control of the BIAcore control 3.1 software (BIACORE, Uppsala, Sweden). Amine-coupling kits and GST capture kits were purchased from BIACORE. The following is common to all experiments. Approximately 5000 resonance units (RU) of anti-GST antibodies were immobilized onto flow cell surfaces of CM4 sensor chips (BIACORE) using amine coupling chemistry. Prior to experiments, the binding capacity of immobilized antibodies was tested by capturing GST. Unless otherwise stated, experiments were carried out at 25 °C, using HBS supplemented with 10 mm MgCl2 as running buffer. GST and the GST-tagged activators were separately immobilized onto the sensor chip, after which 75 μl of target protein was injected at a rate of 20 μl/min. After each cycle, flow cell surfaces were regenerated by two pulses of regeneration buffer (10 mm glycine, pH 2.2) (BIACORE). All response data were collected at a rate of 1 Hz, manually aligned along the x-axis and y-axis, and processed by double referencing (i.e. subtraction of background binding to the affinity tag (GST), as well as adjustment for flow cell-specific bulk effects by subtraction of buffer injection). Curve fitting was performed using BIAevaluation 3.0.2 software (BIACORE) and a sequential two-step model as previously described (8Hermann S. Berndt K.D. Wright A.P. J. Biol. Chem. 2001; 276: 40127-40132Abstract Full Text Full Text PDF PubMed Scopus (40) Google Scholar). Comparison of wild-type and mutant VP16AD was performed on adjacent flow cells. Characterization of the VP16AD-TBP interaction was performed in duplicate samples on adjacent flow cells, using 0.83, 1.7, and 3.3 μm TBP. One injection of buffer control was run prior to injection of target protein and used for double referencing. Characterization of the Gal4AD-TBP, Gal4AD-Swi1ABD, and VP16AD-Swi1ABD interactions was performed on flow cell 2, using flow cell 1 for the GST reference, with the following concentrations of target proteins: 0.21, 0.43, 0.85, 1.7, and 3.4 μm Swi1ABD; and 0.21, 0.41, 0.83, 1.7, and 3.3 μm TBP. Three consecutive injections of buffer control were run prior to injection of dilution series of target proteins, which were followed by a fourth buffer control injection. An average of three buffer injections was used for double referencing. The running buffer was supplemented with 2% glycerol, and analyte samples were diluted to 2% glycerol prior to injection. Temperature experiments on Gal4AD-Swi1ABD were performed using the running buffer described above containing 300 mm NaCl. Reproducibility was assessed as follows. Results obtained by repeating the 150 mm NaCl experiment at 25 °C on Gal4AD-TBP at different time points and on different sensor chips varied by <11% for the fast phase, 18% for the slow phase, and 27% for overall affinity. For duplicates on parallel flow cells in VP16AD-TBP experiments, results generally varied by <11% for the fast phase, 26% for the slow phase, and 26% for overall affinity. Acidic Activators Bind Target Proteins in Two Major Kinetic Steps—We used SPR to monitor the interaction of target proteins with activation domains that were immobilized on the surface of a sensor chip. Using this technique, it is possible to measure the time-dependent association of target proteins in the buffer stream with immobilized activation domains as they flow over the chip surface. Furthermore, because the continuous flow of target protein solution can be exchanged for buffer alone following association, it is possible to measure the dissociation kinetics of complexes that have been formed on the chip surface. The plots (sensograms) are then subjected to regression analysis in order to extract the kinetic and equilibrium constants according to a selected binding model. To determine whether acidic activators bind to target proteins by a mechanism similar to that reported for the c-Myc-TBP interaction, we measured the kinetics of VP16AD binding to TBP as well as protein segments constituting the ABDs of Swi1 and Snf5. Fig. 1 displays the characteristic bi-phasic time course of VP16AD interacting with all three target proteins. The mutant VP16Δ456, which has impaired transcriptional activity (18Triezenberg S.J. Kingsbury R.C. Mcknight S.L. Genes Dev. 1988; 2: 718-729Crossref PubMed Scopus (596) Google Scholar, 37Berger S.L. Cress W.D. Cress A. Triezenberg S.J. Guarente L. Cell. 1990; 61: 1199-1208Abstract Full Text PDF PubMed Scopus (194) Google Scholar) and displays severely reduced affinity for Swi1 and Snf5 (33Neely K.E. Hassan A.H. Brown C.E. Howe L. Workman J.L. Mol. Cell. Biol. 2002; 22: 1615-1625Crossref PubMed Scopus (146) Google Scholar, 34Prochasson P. Neely K.E. Hassan A.H. Li B. Workman J.L. Mol. Cell. 2003; 12: 983-990Abstract Full Text Full Text PDF PubMed Scopus (75) Google Scholar), is included as a control. As expected, this mutant (Fig. 1, gray line) also produces a significantly reduced SPR response. A two-step model reproduces the experimental data well (Fig. 1, dashed line) and demonstrates that activator-target complex formation is consistent with an initial fast step followed by a subsequent slower step. Increased Temperature Favors the Slow Phase but Generally Does Not Affect the Fast Initial Phase—The kinetics of activator binding to a dilution series of target proteins was measured as a function of temperature. Fig. 2 provides an overview of the binding data by showing sensograms for the highest concentration of the respective target proteins interacting with each activator at the extremes of temperature tested. All activator-target combinations interact with bi-phasic kinetics under all conditions tested. Higher temperature (black line) significantly increases the rate of the slow association phase but does not markedly affect the dissociation rate or the fast association phase, resulting in an increased rate of complex formation. To investigate the nature of the respective interaction phases, equilibrium affinity constants for initial and subsequent phases were obtained as a function of temperature and subjected to a van't Hoff analysis. Increased temperature caused a progressive increase in association during the slow phase for all activator-target combinations, and the positive sign of the van't Hoff enthalpy indicates that the slow phase is entropy-driven (Fig. 3, A–D; Table I). The fast phase was not significantly affected by temperature, except in the case of Gal4AD binding to Swi1ABD, in which the fast phase displays a clear trend that is opposite to that of the slow phase (Fig. 3B; Table I).Table Ivan't Hoff enthalpies calculated from data shown in Figs.3and6Activator-target interactionΔHslowΔHfastΔHoverallkJ × mol-1kJ × mol-1kJ × mol-1Gal4AD-TBP52 ± 181 ± 452 ± 16VP16AD-TBP39 ± 4-3 ± 835 ± 12Gal4AD-SwilABDa300 mm NaCl.172 ± 53-53 ± 8118 ± 45VP16AD-SwilABD72 ± 1416 ± 1393 ± 9a 300 mm NaCl. Open table in a new tab Increased Ionic Strength Inhibits the Fast Initial Phase but Favors the Subsequent Slow Phase—The kinetics of activator binding to a dilution series of target proteins was measured as a function of NaCl concentration. An overview of the binding data is shown by the sensograms for the highest concentration of the respective target proteins interacting with each activator at the extremes of NaCl concentrations tested (Fig. 4). As shown for the effect of temperature (Fig. 2), the interaction kinetics of each of the activator-target combinations remains bi-phasic under all the conditions studied. Increased ionic strength (gray line) significantly reduces the amplitude of the overall response without significantly affecting the relative contribution of the fast and slow association phases, as would be expected if the initial step was largely electrostatic in nature. When plotted as the natural logarithms of the calculated affinity constants for each binding phase as a function of NaCl concentration, the data demonstrate that increasing ionic strength results in a reduction of the magnitude of the initial fast phase for all activator-target combinations (Fig. 5, A–D). Contrary to this inhibitory effect on the initial fast phase, increasing ionic strength favored the subsequent slow phase. Effect of Increased Ionic Strength and Temperature on the Overall Affinity of Acidic Activators for Target Proteins—The different nature of electrostatic and hydrophobic interactions makes it difficult to predict the effect of increased ionic strength and temperature on the overall affinity of activator-target interactions. Fig. 6A shows that the overall affinities for all the interactions tested increase with increased temperature. The slopes of these plots again yield a positive van't Hoff enthalpy for binding. The overall reaction is therefore also entropy-driven. The effect of increasing ionic strength on overall affinity (Fig. 6B) is more heterogeneous. Gal4AD displayed an increased overall affinity for both TBP and Swi1ABD with increasing ionic strength. VP16AD behaves differently when binding Swi1ABD and TBP. The VP16AD-Swi1ABD interaction is similar to the Gal4AD pattern with both targets, although in the case of VP16AD binding to Swi1ABD, the increase in overall affinity with increased ionic strength is subtle. However, the interaction of VP16AD with TBP is sensitive to increasing ionic strength and thus shows a trend opposite to that observed for the other interactions. Here we have tested the generality of the target-induced folding model, using the activation domains of two naturally occurring acidic activators, Gal4 and VP16, which are frequently used as models in studies of activator function. In addition to the well-established binding partner TBP, two recently defined activator-binding domains within the Swi1 and Snf5 subunits of the Swi/Snf chromatin remodeling complex were also studied. The target-induced folding model that we proposed previously to account for the interaction between c-Myc and TBP entails three main requirements. First, the interaction between activator and target occurs in two main steps. Second, the initial step is rapid and dependent on electrostatic interactions between the proteins. Third, the second interaction step is slower and entropy-driven, suggesting the involvement of protein folding. All three of these conditions are fulfilled by all the interactions between the acidic activators and target proteins tested here. We therefore propose that the target-induced protein folding model is applicable to a broad range of activator-target interactions. It has been suggested that activation domains of acidic activators, including VP16 and Gal4, function as "acid blobs" that recruit target proteins to promoters via low affinity, nonspecific electrostatic interactions (20Sigler P.B. Nature. 1988; 333: 210-212Crossref PubMed Scopus (300) Google Scholar, 21Ansari A.Z. Reece R.J. Ptashne M. Proc. Natl. Acad. Sci. U. S. A. 1998; 95: 13543-13548Crossref PubMed Scopus (48) Google Scholar). Our results provide a more complete context for understanding the role played by electrostatic forces in interactions between acidic activation domains and the target factors they recruit. According to our model, electrostatic interactions dominate during the initial binding phase, but they generally have a subordinate role in the subsequent entropy-driven phase, where formation of the final complex depends on hydrophobic interactions. This is consistent with our observation that increased temperature, which increases the efficiency of the entropy-driven step, stabilizes formation of the final complex. Our model is consistent with genetic studies showing both the importance of overall acidity and the crucial role played by specific individual hydrophobic but not individual acidic residues in activation domain function (7Almlöf T. Gustafsson J Å. Wright A.P.H. Mol. Cell. Biol. 1997; 17: 934-945Crossref PubMed Scopus (63) Google Scholar, 22Almlöf T. Wright A.P.H. Gustafsson J. Å. J. Biol. Chem. 1995; 270: 17535-17540Abstract Full Text Full Text PDF PubMed Scopus (89) Google Scholar, 23Cress W.D. Triezenberg S.J. Science. 1991; 251: 87-90Crossref PubMed Scopus (324) Google Scholar, 30Melcher K. Johnston S.A. Mol. Cell. Biol. 1995; 15: 2839-2848Crossref PubMed Scopus (146) Google Scholar). We conclude that whereas electrostatic interactions might sometimes increase the rate of complex formation, the affinity of interactions between acidic activators and the factors they recruit depends on hydrophobic interactions that are likely to be associated with folding of the participating activation domains. The target-induced folding model suggests that target proteins exert a dominant influence on the ultimate state of the activator-target complex, and thus one might expect to see characteristic binding patterns associated with at least some target proteins. Such a pattern was observed for TBP, for which all changes in experimental variables had essentially the same effects on the binding pattern of both VP16AD and Gal4AD (see Figs. 2 and 4). This suggests that the activators may have similar contacts on TBP, a notion that is supported by previous studies (30Melcher K. Johnston S.A. Mol. Cell. Biol. 1995; 15: 2839-2848Crossref PubMed Scopus (146) Google Scholar, 38Kim T.K. Hashimoto S. Kelleher R.J. Flanagan P.M. Kornberg R.D. Horikoshi M. Roeder R.G. Nature. 1994; 369: 252-255Crossref PubMed Scopus (102) Google Scholar). In light of these results, a picture emerges of a relatively predefined TBP scaffold, providing a common surface specialized in activator recognition. Although all the interactions studied here conform to the two-step target-induced folding interaction model, differential contributions of electrostatic and hydrophobic interactions could be responsible for some interesting differences between the different activator-target interactions. One example is the different behavior of the overall affinities for the VP16AD-TBP and Gal4AD-TBP complexes in response to ionic strength. This behavior correlates with previous affinity data for TBP, measured using other techniques (29Stringer K.F. Ingles C.J. Greenblatt J. Nature. 1990; 345: 783-786Crossref PubMed Scopus (408) Google Scholar, 30Melcher K. Johnston S.A. Mol. Cell. Biol. 1995; 15: 2839-2848Crossref PubMed Scopus (146) Google Scholar). Unlike VP16AD, Gal4AD displays increased overall affinity for both target proteins in increased ionic strength, which suggests that Gal4AD may have some additional unfavorable electrostatic interactions to overcome upon complex formation, compared with VP16AD. Furthermore, the observation that Swi1ABD, but not TBP, can support an increased overall affinity with both of these activators at high ionic strength helps to illuminate the individual influence of a target on activator binding despite some potentially unfavorable interactions. Interestingly, whereas the effect of ionic strength on overall affinity appears to depend on both activator and target protein, the magnitude of the effect of temperature appears to depend entirely on the target protein (see Fig. 6, A and B). Higher temperature has a stronger positive effect on the activator complexes with Swi1 than it does with TBP. These binding characteristics of Swi1 could be interpreted as the activator-binding surface being more hydrophobic in nature. Upon activator binding, repulsive electrostatic interactions dominate, compared with TBP. However, because there are multiple ways that both electrostatic and hydrophobic interactions could combine at the interaction interfaces producing the observed differences between activator-target complexes, it is difficult to predict a priori the nature of the interaction surfaces. In summary, our results indicate that the acidic activator proteins Gal4 and VP16 share a common target protein binding mechanism that is consistent with binding-induced folding of the activator. We propose that, in general, the role of the abundant acidic residues of such activators is primarily to promote a rapid, rather unspecific, initial contact and that specificity relies on hydrophobic interactions that determine the stability of the final complex and the rate with which it forms. However, as shown here, the relative contribution of electrostatic and hydrophobic interactions to complex stability varies for particular activator-target combinations. The model we propose provides a framework that integrates the previously demonstrated importance of both acidic and bulky hydrophobic amino acid residues for target recruitment and the activation potential of acidic activators (11Leuther K.K. Salmeron J.M. Johnston S.A. Cell. 1993; 72: 575-585Abstract Full Text PDF PubMed Scopus (105) Google Scholar, 23Cress W.D. Triezenberg S.J. Science. 1991; 251: 87-90Crossref PubMed Scopus (324) Google Scholar, 25Regier J.L. Shen F. Triezenberg S.J. Proc. Natl. Acad. Sci. U. S. A. 1993; 90: 883-887Crossref PubMed Scopus (226) Google Scholar, 26Sullivan S.M. Horn P.J. Olson V.A. Koop A.H. Niu W. Ebright R.H. Triezenberg S.J. Nucleic Acids Res. 1998; 26: 4487-4496Crossref PubMed Scopus (57) Google Scholar, 30Melcher K. Johnston S.A. Mol. Cell. Biol. 1995; 15: 2839-2848Crossref PubMed Scopus (146) Google Scholar). These results suggest that target-induced folding may be a general mechanism by which transcriptional components are recruited to promoters by naturally occurring activators. We thank Kristmundur Sigmundsson (Karolinska Institutet) for valuable discussions and advice.
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