Disorder-to-order transition underlies the structural basis for the assembly of a transcriptionally active PGC-1α/ERRγ complex - PubMed (original) (raw)

Disorder-to-order transition underlies the structural basis for the assembly of a transcriptionally active PGC-1α/ERRγ complex

Srikripa Devarakonda et al. Proc Natl Acad Sci U S A. 2011.

Abstract

Peroxisome proliferator activated receptor (PPAR) γ coactivator-1α (PGC-1α) is a potent transcriptional coactivator of oxidative metabolism and is induced in response to a variety of environmental cues. It regulates a broad array of target genes by coactivating a whole host of transcription factors. The estrogen-related receptor (ERR) family of nuclear receptors are key PGC-1α partners in the regulation of mitochondrial and tissue-specific oxidative metabolic pathways; these receptors also demonstrate strong physical and functional interactions with this coactivator. Here we perform comprehensive biochemical, biophysical, and structural analyses of the complex formed between PGC-1α and ERRγ. PGC-1α activation domain (PGC-1α(2-220)) is intrinsically disordered with limited secondary and no defined tertiary structure. Complex formation with ERRγ induces significant changes in the conformational mobility of both partners, highlighted by significant stabilization of the ligand binding domain (ERRγLBD) as determined by HDX (hydrogen/deuterium exchange) and an observed disorder-to-order transition in PGC-1α(2-220). Small-angle X-ray scattering studies allow for modeling of the solution structure of the activation domain in the absence and presence of ERRγLBD, revealing a stable and compact binary complex. These data show that PGC-1α(2-220) undergoes a large-scale conformational change when binding to the ERRγLBD, leading to substantial compaction of the activation domain. This change results in stable positioning of the N-terminal part of the activation domain of PGC-1α, favorable for assembly of an active transcriptional complex. These data also provide structural insight into the versatile coactivation profile of PGC-1α and can readily be extended to understand other transcriptional coregulators.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.

Fig. 1.

Molecular determinants of specificity and affinity for the binary complex. A schematic representation of (A) ERRγ and PGC-1α domains and (B) three NR boxes/LXXLL motifs (L1, L2, and L3). Interaction studies using GST-fusion fragments of (C) ERRγ and 35S-labeled PGC-1α or (D) PGC-1α and 35S-labeled ERRγ.

Fig. 2.

Fig. 2.

HDX analysis of the ERRγLBD/PGC-1α activation domain interaction. HDX analysis of ERRγLBD interaction was performed with five distinct constructs of PGC-1α activation domain. (A) ERRγLBD ± PGC1α220. (B) ERRγLBD ± PGC1α (136–220) WT, L2A, L3A, and L2L3A. The differential HDX between apo ERRγLBD and PGC-1α bound LBD is mapped onto PDB ID code 1KV6. The difference in the mean HDX across six time points for coactivator bound and unbound LBD is represented as percent change and colored according to the key. Gray, no change in HDX between bound and unbound LBD; light to dark blue, slower rates of HDX between compared conditions; yellow to red, faster rates of HDX between compared conditions.

Fig. 3.

Fig. 3.

Biophysical properties of the binary complex. (A) Representative SEC-MALS analyses showing elution profiles for PGC1α220 (red), ERRγLBD (blue), and the binary complex (pink) on a Superdex 200 10/300 column at room temperature. Absorbance profiles are shown in relative units at 280 nm (left y axis). Shown as colored circles on each elution profile are the masses determined from MALS analysis; the right y axis denotes mass in daltons. (B) Sedimentation coefficient distribution [c(S)] analysis of sedimentation velocity data for PGC1α220 (red line, 38 μM at 4 °C), ERRγLBD (blue line, 61 μM at 20 °C), and the binary complex (pink line, 28 μM at 20 °C).

Fig. 4.

Fig. 4.

Thermodynamic and structural stability of the binary complex. (A) Far-UV CD spectra of PGC1α220 (red), ERRγLBD (blue), and binary complex (pink). Spectra were normalized to molar ellipticity, secondary structure was quantified using CDFIT and summarized in Table 2. (B) Thermal denaturation of ERRγLBD (●) and binary complex (▪). The CD signal at 222 nm was monitored as a function of temperature. (C) Chemical denaturation ERRγLBD (●) and binary complex (▪). Intrinsic tryptophan fluorescence was monitored as a function of increasing urea concentration. T m and D m values were calculated as described in Materials and Methods and are summarized in Table 3.

Fig. 5.

Fig. 5.

Solution properties of the binary complex and its individual components determined using SAXS. (A) Shape distribution [P(r)] functions derived from SAXS analysis for PGC1α220 (red), ERRγLBD (blue), and the binary complex (pink). (B) Kratky plot analysis for the proteins examined, where the intensity of scattering is plotted as IQ_2 versus Q. I is the scattering intensity and Q is scattering angle (Q = 4_π sin θ/λ). (C) Porod–Debye plot of the SAXS data for the samples examined in the study, shown as _IQ_4 versus _Q_4.

Fig. 6.

Fig. 6.

Shape reconstruction for PGC1α220 from SAXS data using EOM analysis. (A) EOM fit (red line) to the SAXS data for PGC1α220 (open squares), with _χ_2 of 1.14 for the best selected pool solution. (B) R g distributions for the pool (black) and optimized (red) ensembles generated by EOM analysis. (C) Representative gallery of bead models for PGC1α220 derived from EOM analysis. The bead radius used in these models is 3.4 Å, and this figure was generated using PyMOL.

Fig. 7.

Fig. 7.

Shape reconstruction of ERRγLBD and its binary complex with PGC1α220. (A, Left) GASBOR fit (blue line) to primary scattering data (black squares) for ERRγLBD. (Right) SAXS envelope calculated using GASBOR and rigid body docking of structural model of ERRγLBD into the envelope (B, Left) GASBOR fit (red line) to primary scattering data (black squares) for binary complex. (Right) SAXS envelope of the binary complex calculated using GASBOR. (C, Left) MONSA fit to primary data (ERRγLBD, blue line and black squares; binary complex, red line and black squares), (Right) SAXS envelope of the binary complex calculated using MONSA.

Fig. 8.

Fig. 8.

Predicted interaction model for the binary complex. A structural model for ERRγLBD and PGC1α220 interaction proposed based on a summary of our data. HDX data is mapped onto the ERRγLBD dimer (PDB ID code 1KV6) to indicate regions of the LBD affected by the interaction and PGC1α220 is shown in orange.

Similar articles

Cited by

References

    1. Lin J, Handschin C, Spiegelman BM. Metabolic control through the PGC-1 family of transcription coactivators. Cell Metab. 2005;1:361–370. - PubMed
    1. Ventura-Clapier R, Garnier A, Veksler V. Transcriptional control of mitochondrial biogenesis: The central role of PGC-1alpha. Cardiovasc Res. 2008;79:208–217. - PubMed
    1. Jornayvaz FR, Shulman GI. Regulation of mitochondrial biogenesis. Essays Biochem. 2010;47:69–84. - PMC - PubMed
    1. Olesen J, Kiilerich K, Pilegaard H. PGC-1alpha-mediated adaptations in skeletal muscle. Pflugers Arch. 2010;460:153–162. - PubMed
    1. Giguere V. Transcriptional control of energy homeostasis by the estrogen-related receptors. Endocr Rev. 2008;29:677–696. - PubMed

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources