Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Mar;567(7746):56-60.
doi: 10.1038/s41586-019-0988-7. Epub 2019 Feb 27.

Structure of the IFNγ receptor complex guides design of biased agonists

Affiliations

Structure of the IFNγ receptor complex guides design of biased agonists

Juan L Mendoza et al. Nature. 2019 Mar.

Abstract

The cytokine interferon-γ (IFNγ) is a central coordinator of innate and adaptive immunity, but its highly pleiotropic actions have diminished its prospects for use as an immunotherapeutic agent. Here, we took a structure-based approach to decoupling IFNγ pleiotropy. We engineered an affinity-enhanced variant of the ligand-binding chain of the IFNγ receptor IFNγR1, which enabled us to determine the crystal structure of the complete hexameric (2:2:2) IFNγ-IFNγR1-IFNγR2 signalling complex at 3.25 Å resolution. The structure reveals the mechanism underlying deficits in IFNγ responsiveness in mycobacterial disease syndrome resulting from a T168N mutation in IFNγR2, which impairs assembly of the full signalling complex. The topology of the hexameric complex offers a blueprint for engineering IFNγ variants to tune IFNγ receptor signalling output. Unexpectedly, we found that several partial IFNγ agonists exhibited biased gene-expression profiles. These biased agonists retained the ability to induce upregulation of major histocompatibility complex class I antigen expression, but exhibited impaired induction of programmed death-ligand 1 expression in a wide range of human cancer cell lines, offering a route to decoupling immunostimulatory and immunosuppressive functions of IFNγ for therapeutic applications.

PubMed Disclaimer

Figures

Extended Data Fig. 1
Extended Data Fig. 1. Characterization of IFNγ complex formation and stabilizing mutations.
a, Schematic for quantifying the homodimerization of either IFNγR1 (top) or IFNγR2 (bottom) using dye-labelled anti-GFP nanobodies labelled with Rho11 and DY647. b, Homodimerization of IFNγR1 in the absence and presence of ligand. Data are mean ± s.e.m.; n = 8 (−IFNγ) and 12 (+IFNγ); n refers to biologically independent samples. c, Homodimerization of IFNγR2 in absence and presence of ligand. Data are mean ± s.e.m.; where n = 5 (−IFNγ) and 16 (+IFNγ); n refer to biologically independent samples. d, IFNγR1 displays on the surface of the yeast. Second from left, anti-Myc-647 antibody; far left, steptavidin–Alexa Fluor 647. The high avidity form of IFNγR2 only binds to IFNγR1 in the presence of IFNγ (far right) and does not bind IFNγR1 alone (second from right). Data are representative of at least 3 biologically independent experiments. e, Sequence alignment of IFNγR1 genes including 13 first-generation variants and the shuffled IFNγR1 F05 variant relative to wild-type. IFNγR1 F05 combines six mutations including Q167K and M161K. The combination of Q167K and M161K is not seen in any single first-generation mutant.
Extended Data Fig. 2
Extended Data Fig. 2. Purification and electron density maps of the IFNγ hexameric signalling complex.
a, SEC (Superdex S200 column) of the 2:2:2 IFNγ–IFNγR1–IFNγR2 complex and SDS–PAGE gels of the deglycosylated (top, left gel) and fully glycosylated (top, right gel) forms. Data shown are representative of at least 3 biologically independent experiments. mAU, milli absorbance units. b, Electron density maps showing interactions at site 2 (top) and site 3 (bottom) in the deglycosylated complex. For each pair of site 2 or site 3 panels, the left panel shows a simulated annealing composite omit map (grey) contoured at 1σ, and the right panel shows a 2mFoDFc map (blue) calculated using phases from the final refined model and contoured at 1σ. IFNγ (green) engages IFNγR2 (cyan) at site 2, whereas the stems of IFNγR1 F05 (yellow) and IFNγR2 interact at site 3.
Extended Data Fig. 3
Extended Data Fig. 3. Quantification of IFNγR2(T168N) glycoforms by mass spectroscopy.
a, The mutant IFNγR2(T168N) protein was expressed in HEK293S GnTI cells and purified by SEC. The SEC profile is shown (left) with the corresponding fractions on SDS–PAGE (right). Lane 1 shows the sample loaded on the SEC column, lane 2 shows the Mark 12 protein ladder, and lanes 3–9 are fractions 14–20. Data are representative of at least 3 biologically independent experiments. b, The protein coverage map shows sequence coverage of 76.82% for the entire IFNγR2(T168N) protein including the peptide of interest, containing N168, which is underlined. This peptide was detected as a glycopeptide with several glycoforms as quantified in Fig. 3d. Mappings highlighted in green indicate high confidence with a false discovery rate (FDR) below 1% and yellow indicates a FDR of 1–5%. Carbamidomethyl (C) and glycosylation (G) sites are indicated above the site of modification. Confidence levels were determined as previously described. c, MS2 spectra confirming that the ion used for the EICs shown in Fig. 3d is the peptide SSPFDIADNSTAF from IFNγR2(T168N) modified with a HexNAc2Hex5 glycan attached to N168. The data shown are for a single experiment.
Extended Data Fig. 4
Extended Data Fig. 4. Disrupting IFNγR2 binding and characterization of IFNγ partial agonists.
a, The structure of IFNγ (blue and tan cartoon) binding site for IFNγR2 (interacting loops are shown in green). Based on the hexameric complex, positions in IFNγ at the IFNγR2 binding interface were identified to be important for binding to IFNγR2. The location of IFNγ mutations K74A, E75Y, and N83R are shown as sticks coloured in red. b, When complexed with IFNγ R1, the IFNγ triple mutant (K74A/E75Y/N83R) results in the loss of detectable binding to IFNγR2 (up to 100 μM) as determined by SPR. The titration data are from a single experiment. c, Relative co-tracking of binding of IFNγR1 (left panel) and IFNγR2 (right panel) for wild-type IFNγ and variants. GIFN2, one IFNγR1 and one IFNγR2 binding in cis; GIFN3, two IFNγR1 molecules bound; GIFN4, reduced affinity for both IFNγR1 and IFNγR2 (see Extended Data Fig. 5). Data are mean ± s.e.m.; n is indicated over each bar; n refers to the number of biologically independent samples. d, STAT1 activation of GIFN4 in Hap1 cells. Curve was fit to a first-order logistic model. Data are mean; n = 2 biologically independent samples. e, Quantification of MHC class I expression by qPCR using primers against HLA chain b in A549 treated cells. Data are mean ± s.e.m.; n = 3 biologically independent experiments. f, Dendritic cells purified from whole blood were treated for 48 h with either wild-type IFNγ or the partial agonists for 48 h; these agonists upregulate MHC class I antigen expression as quantified by fluorescently labelled antibody (left) or PD-L1 (right). Data shown are for ligand concentrations of 0.1, 0.5, 2.5, 12.5 and 62.5 nM (left to right, respectively, for each agonist). Data are mean ± s.e.m.; n = 3 biologically independent experiments. g, Using the MHC class I and PD-L1 expression data (f and Fig. 5b), the ratio of MHC I:PD-L1 induction was determined for each protein concentration relative to wild-type. Left, dendritic cells; right, A549 cells. Data are mean ± s.e.m.; n = 3 biologically independent experiments. h, Biased MHC I:PD-L1 expression for monocytes (right) and macrophages (left) isolated from PBMCs. Data as shown are for protein concentrations of 0.1, 0.5, 2.5, 12.5 and 62.5 nM (left to right, respectively, for each agonist). Data are mean ± s.e.m.; n = 6 independent samples. i, Cytokine secretion profile of IFNγ and partial agonists for PBMCs treated with 100 nM of each protein for 24 h. Shown are the mean expression of 36 secreted cytokines that are significantly different (P < 0.05) between the wild-type and PFA-treated control. Expression of IL-10, IL-12P70, IL-2, IP-10, MIG and IL-23 are indicated in text or asterisks aligned below the text. Data shown are for n = 2 biologically independent samples, each assayed in triplicate. P values were determined using the Student’s t-test with a two-tailed distribution of a two-sample heteroscedastic test.
Extended Data Fig. 5
Extended Data Fig. 5. Design and biochemical characterization of GIFNs.
a, Diagram showing the strategy for expression and purification of heterodimeric IFNγ variants. The asymmetric variants containing three tags were expressed as single polypeptides in Hi5 insect cells. The proteins were first harvested from the secreted medium with a C-terminal 8× His tag. Proteins eluted from nickel resin were then treated with 1:100 (by mass) human rhinovirus 3C protease for 24 h at 4 °C to cleave the 3C protease tag. The 3C tag is flanked by Gly-Gly-Gly-Ser motifs at both ends (G3S-3C-G3S) to ensure accessibility of the protease site between the two chains of IFNγ. The cleaved proteins were then purified using the N-terminal protein C-tag and a final 8× His tag purification to ensure isolation of the correctly paired heterodimeric IFNγ proteins. b, Table of mutations for each of the GIFN proteins, indicating the affected receptor binding sites. GIFN2, one IFNγR1 and one IFNγR2 binding in cis; GIFN3, two IFNγR1 molecules bound; GIFN4, reduced affinity for both IFNγR1 and IFNγR2. c, SEC profiles and SDS–PAGE gel fractions for 200 μg wild-type IFNγ (black) or equal molar quantities of GIFN1 (purple), GIFN2 (red), GIFN4 (orange), IFNγR1 F05 (grey), and IFNγR2 (green). Individual proteins have been purified and analysed by SEC at least three times. d, e, To determine the receptor-binding properties of the GIFN proteins, the shifts in the SEC profiles and gels were compared relative to the wild-type protein as described for c except IFNs were mixed with equimolar quantities of IFNγR1 F05 (d) or equimolar quantities of both IFNγR1 F05 and IFNγR2 (e). These data are from single experiments except the wild-type experiments which were performed at least three times.
Fig. 1
Fig. 1. Assembly and engineered stabilization of the IFNγ receptor complex.
a, Cell-surface labelling of IFNγR1 (purple) and IFNγR2 (green) using Rho-11 (red circle) and DY647-labelled (blue circle) anti-GFP nanobodies is used to determine receptor dimerization. b, Relative co-tracking of Rho-11–IFNγR1 and DY647–IFNγR2 in the absence and presence of ligand. Data are mean ± s.e.m.; n = 8 (−IFNγ), n = 15 (+IFNγ); n is the number of biologically independent samples. c, Experimental design for engineering higher-affinity IFNγR1 variants. IFNγR1 (grey) is displayed on yeast and, in the presence of unlabelled IFNγ dimer (blue and tan), forms the intermediate 2:2 IFNγ–IFNγR1 complex (middle), enabling detection of variants binding to either tetrameric or monomeric IFNγR2 (green; labelled with streptavidin–Alexa Fluor 647 (SA647)). d, Using this platform, a first-generation library was generated using non-biased error-prone PCR followed by DNA shuffling. e, After a single round of selection, eight clones were titrated to estimate their relative binding to IFNγR2. f, Sites of mutations on IFNγR1 F05 (see Extended Data Fig. 1e).
Fig. 2
Fig. 2. Structure of the IFNγ hexameric complex.
a, The structure of the IFNγ hexameric complex reveals the mechanism of IFNγR2 (green) recognition of IFNγ (blue and tan) and IFNγR1 (grey). IFNγR2 receptors make extensive contacts with the IFNγ dimer at sites 2a and 2b, and site 3a and 3b makes stem–stem contacts with IFNγR1. b, Structure of the IFNλ–IFNλR1–IL-10Rβ signalling complex (PDB: 5T5W) shares a similar geometry with the IFNγ signalling complex. The binding mode of IFNγR2 is nearly identical to that of IL-10Rβ. c, Structure of a type I IFN receptor complex (PDB: 3SE4) with distinct ligand–receptor geometries compared to either type II or III IFNs.
Fig. 3
Fig. 3. Interactions within the IFNγ receptor complex and mechanism of disease mutation.
a, Overview of the IFNγ–IFNγR1 F05–IFNγR2 ternary complex. IFNγ, blue and tan; IFNγR1 F05, grey; IFNγR2, green. b, View of the site 2a (identical to site 2b) contacts between IFNγ and IFNγR2 (left). Detailed view of site 3a (identical to site 3b) between IFNγR1 F05 (grey) and IFNγR2 (green) (right). c, The complex structure places the neoglycosylation site of IFNγR2(T168N) at the site 3a (identical to site 3b) interface. d, IFNγR2(T168N) was expressed in HEK293S GnTI− cells and analysed by nano-liquid chromatography followed by tandem mass spectrometry (LC–MS/MS). The peptide containing N168 was identified (see Extended Data Fig. 3), and relative amounts of various glycoforms were determined by extracted ion chromatograms (EICs). The data shown are for a single experiment. e, The affinity (KD) of IFNγR2 to the 2:2 IFNγ–IFNγR1 intermediate complex was determined to be ~5 μM by SPR (left), whereas the mutant IFNγR2(T168N) results in a loss of binding (right). The titration data are from a single experiment. f, Single-molecule dimerization experiments in cells co-expressing IFNγR1 and IFNγR2(T168N). IFNγ retains binding to IFNγR1 but fails to recruit IFNγR2(T168N). Data are mean ± s.e.m.; n = 14, 15, 13, and 17 (left to right); n is the number of independent experiments.
Fig. 4
Fig. 4. Structure-based design of IFNγ partial agonists with biased signalling outputs.
a, Assembly of the hexameric IFNγ signalling complex can proceed through multiple intermediates. b, Co-tracking of IFNγR1 and IFNγR2 for wild-type and variants of IFNγ. Data are mean ± s.e.m.; n = 8, 15, 16, 16, and 15 independent experiments (left to right). c, IFNγ mutants that stabilized intermediate complexes were assayed for STAT1 activation in Hap1 cells. GIFN2, one IFNγR1 and one IFNγR2 binding in cis; GIFN3, two IFNγR1 bound; GIFN4, reduced affinity for both IFNγR1s and IFNγR2s (see Extended Data Fig. 5). Curves were fitted to a first-order logistic model. Data are mean ± s.e.m.; n = 3 biologically independent experiments. d, Heat map depicting the relative expression (log2[change in expression]) of 1,000 genes from the human transcriptome. e, Correlations in relative expression of wild-type IFNγ and GIFNs for all genes. n = 2 independent biological experiments. f, Principal component analysis (PCA) of the top 600 genes induced by IFNγ, were compared to GIFN2–4. n = 2 biologically independent experiments. g, Genes, including CD274 (which encodes PD-L1), that have significantly lowered expression with GIFN4 relative to wild-type IFNγ (top). Genes, including HLA-A, that are robustly expressed with both wild-type IFNγ and GIFN4 (bottom panel).
Fig. 5
Fig. 5. Decoupled expression of MHC I versus PD-L1 in response to IFNγ or partial agonists.
a, b, A549 cells were treated with either IFNγ (wild-type) or partial agonists for 48 h. Upregulation of MHC class I antigen and PD-L1 expression were quantified by reverse transcription with quantitative PCR (RT–qPCR) (a; ligand concentration, 62.5 nM; mean ± s.e.m., n = 3 biologically independent experiments), by using fluorescently labelled HLA-ABC antibody (b, left; ligand concentrations 0.1, 0.5, 2.5, 12.5 and 62.5 nM (left to right, respectively, for each agonist); mean ± s.e.m.; n = 6 independent samples), and using fluorescently labelled PD-L1 antibody (b, right). MFI, median fluorescence intensity. c, d, Six additional cancer cell lines (Hap1, MeWo, HT-29, Hep G2, HeLa, and Panc-1) were screened for MHC I:PD-L1 bias as in b, but after 24 h treatment (ligand concentrations 0.1, 0.5, 2.5, 12.5 and 62.5 nM (left to right, respectively, for each agonist); mean ± s.e.m.; n = 8 independent samples).

Comment in

References

    1. Pace JL, Russell SW, LeBlanc PA & Murasko DM Comparative effects of various classes of mouse interferons on macrophage activation for tumor cell killing. J. Immunol 134, 977–981 (1985). - PubMed
    1. Nakajima C et al. A role of interferon-γ (IFN-γ) in tumor immunity: T cells with the capacity to reject tumor cells are generated but fail to migrate to tumor sites in IFN-γ-deficient mice. Cancer Res 61, 3399–3405 (2001). - PubMed
    1. Stark GR, Kerr IM, Williams BR, Silverman RH & Schreiber RD How cells respond to interferons. Annu. Rev. Biochem 67, 227–264 (1998). - PubMed
    1. Mandai M et al. Dual faces of IFNγ in cancer progression: a role of PD-L1 induction in the determination of pro- and antitumor immunity. Clin. Cancer Res 22, 2329–2334 (2016). - PubMed
    1. Yphantis DA & Arakawa T Sedimentation equilibrium measurements of recombinant DNA derived human interferon gamma. Biochemistry 26, 5422–5427 (1987). - PubMed

Publication types

MeSH terms