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Affinity-matured DLL4 ligands as broad-spectrum modulators of Notch signaling

Nature Chemical Biology volume 19, pages 9–17 (2023)Cite this article

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Abstract

The Notch pathway regulates cell fate decisions and is an emerging target for regenerative and cancer therapies. Recombinant Notch ligands are attractive candidates for modulating Notch signaling; however, their intrinsically low receptor-binding affinity restricts their utility in biomedical applications. To overcome this limitation, we evolved variants of the ligand Delta-like 4 with enhanced affinity and cross-reactivity. A consensus variant with maximized binding affinity, DeltaMAX, binds human and murine Notch receptors with 500- to 1,000-fold increased affinity compared with wild-type human Delta-like 4. DeltaMAX also potently activates Notch in plate-bound, bead-bound and cellular formats. When administered as a soluble decoy, DeltaMAX inhibits Notch in reporter and neuronal differentiation assays, highlighting its dual utility as an agonist or antagonist. Finally, we demonstrate that DeltaMAX stimulates increased proliferation and expression of effector mediators in T cells. Taken together, our data define DeltaMAX as a versatile tool for broad-spectrum activation or inhibition of Notch signaling.

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Fig. 1: Yeast display selection strategy for affinity maturation of human DLL4.
Fig. 2: Biophysical characterization of the DeltaMAX variant.
Fig. 3: DeltaMAX is a more potent Notch agonist than WT DLL4.
Fig. 4: DeltaMAX is a pan-Notch inhibitor.
Fig. 5: DeltaMAX stimulation increases proliferation and expression of activation markers in human CD8+ T cells.
Fig. 6: Soluble DeltaMAX promotes neuronal differentiation.

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Data availability

The authors declare that all the data generated in this study are available within the article, the Extended Data information and Figs. Source data are also provided with this article and additional raw data are available from the corresponding author upon request. For Figs. 1a, 2a, Extended Data Figs. 1a, 2a and 3, the crystal structures Notch1:JAG1 (PDB: 5UK5) and Notch1:DLL4 (PDB: 4XL1) were used and they can be accessed from the Protein Data Bank.

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Acknowledgements

We thank Dr. E. Lau, G. Watson and D. Lester for assistance in generating DLL4 stable cell lines. We also thank Dr. T. Tran from Moffitt Chemical Biology Core for helping with DSF studies and Dr. Q. Ming for helpful suggestions. Parts of Fig. 5a were drawn using pictures from Servier Medical Art; Servier Medical Art by Servier is licensed under a Creative Commons Attribution 3.0 Unported License. Figure 6a was created with BioRender. This project was supported by R35GM133482 (NIH) and an award from the Rita Allen Foundation (D.G.P. and V.C.L.), the Sigrid Juselius Foundation (D.A.), R35CA220340 (NIH) (S.C.B.) R01CA184185 (NIH), R01CA233512 (NIH); R01CA262121 (NIH); P01CA250984 (NIH) Project no. 4; and P30CA076292 (NIH); and Florida Department of Health grant no. 20B04 (P.C.R. and S.D.). Support for shared resources was provided by the Moffitt Cancer Center (support grant No. NIH P30CA076292). This research was supported by the Stanford Maternal and Child Health Research Institute (K.M.L.). K.M.L. is a Packard Fellow, Pew Scholar, HFSP Young Investigator and The DiGenova Endowed Faculty Scholar.

Author information

Authors and Affiliations

  1. Department of Drug Discovery, Moffitt Cancer Center, Tampa, FL, USA

    David Gonzalez-Perez, Daniel Antfolk, Elliot Medina & Vincent C. Luca

  2. Department of Immunology, Moffitt Cancer Center, Tampa, FL, USA

    Satyajit Das & Paulo C. Rodriguez

  3. Stanford Institute for Stem Cell Biology & Regenerative Medicine, Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA

    Hadia S. Ahsan, Carolyn E. Dundes, Rayyan T. Jokhai & Kyle M. Loh

  4. Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA

    Emily D. Egan & Stephen C. Blacklow

  5. Department of Cancer Biology, Dana Farber Cancer Institute, Boston, MA, USA

    Stephen C. Blacklow

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  1. David Gonzalez-Perez
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Contributions

V.C.L. and D.G.P. wrote the manuscript. V.C.L., D.G.P, K.M.L. and P.C.R. designed the experiments. D.G.P. performed the protein purifications, yeast display selections, binding studies and signaling assays. S.D. performed and designed the T cell experiments with assistance from P.C.R. E.M. contributed to library design and cloning. D.A. performed Notch activation assays in U2OS and MCF-7 cells, adsorption by ELISA, DLL4-tetramer binding and compared Notch1 expression levels by flow cytometry. E.D.E. and S.C.B. provided U2OS reporter cells and assisted with luciferase experimental procedures. H.S.A., C.E.D, R.T.J and K.M.L. designed and performed the hPSC differentiation experiments. S.C.B., K.M.L., P.C.R. and V.C.L. edited and reviewed the manuscript. V.C.L. supervised and conceived the project.

Corresponding author

Correspondence to Vincent C. Luca.

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Competing interests

V.C.L., P.C.R. and D.G.P., have filed provisional patents describing the engineering and applications of DeltaMAX (application numbers PCT/US2020/041765 and PCT/US2020/030977). V.C.L. is a consultant on an unrelated project for Cellestia Biotech. S.C.B. is on the SAB and receives funding from ERASCA, Inc. for an unrelated project, and is a consultant on unrelated projects for Scorpion Therapeutics, Odyssey Therapeutics, Ayala Pharmaceuticals, MPM Capital and Droia Ventures.

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Extended data

Extended Data Fig. 1 Mutant library design and selection strategy for isolation of affinity-enhancing mutations in DLL4.

a, Table depicting DLL4 interface residue positions and the mutations allowed at each position, and schematic of DLL4 yeast display construct. Yellow stars indicate mutations. Expression of DLL4 was detected by flow with anti-HA tag antibody. b, Flow chart depicting the selection strategy used to isolate high-affinity DLL4 variants. Red arrows and text indicate negative selections. c, Gating strategy for sorting high-affinity binders to Notch3.

Extended Data Fig. 2 Conservation analysis of Site 3 library positions in activating Notch ligands.

a, A structural model depicting amino acid conservation in DLL1, DLL4, JAG1, and JAG2 residues was generated in Consurf using rat JAG1 as a template (PDB ID: 5UK5). b, Identity matrix indicating the sequence identity between human Notch ligands. c, Sequence alignment depicting conservation at each residue position. Residues mutated in the DLL4 mutant library are highlighted in red.

Extended Data Fig. 3 Structural analysis of DeltaMAX mutations.

Cartoon representation showing the structural context of DLL4.v2 mutant in a model of the rat JAG1:Notch1 complex (PDB ID: 5UK5). a, b, c, d, and e are zoom panels depicting the residues that surround the mutated position. Numbers and dashes in (e) are inter-atomic distances atoms measured in angstroms.

Extended Data Fig. 4 Purification of Notch and DLL4 proteins.

(a-b) Size-exclusion chromatography (SEC) chromatograms from the purification of the ligand-binding regions of human Notch1-4 (a) and murine Notch1 (b). All proteins were purified by nickel affinity chromatography followed by size exclusion chromatography using a Superdex S75 column. c, SDS–PAGE gels showing the purity and molecular weight of each Notch construct. d, SEC chromatograms from the purification of WT DLL4, DLL4.v1, DLL4.v2, and DeltaMAX proteins. All proteins were purified by nickel affinity chromatography followed by size exclusion chromatography using a Superdex S200 column. e, SEC chromatograms from the purification of C-termini biotinylated WT DLL4 and DeltaMAX proteins. f, SDS–PAGE gels showing the purity and molecular weight of each DLL4 construct. DLL4-BH3 indicates proteins containing C-terminal biotin acceptor peptides and hexahistadine tags. g, SEC chromatograms from 1 L protein preps were overlaid to highlight the increased yield of recombinant DeltaMAX compared to WT DLL4. h, SDS–PAGE gels showing the elution profile fractions of WT DLL4 and DeltaMAX preps from panel (g). i, Small scale preps of WT DLL4 and DeltaMAX performed in triplicate using the same baculovirus titers. Protein gels in (c), (f), and (h) are representative of multiple replicate preps performed to produce all the proteins for binding and signaling assays (n > three biological replicates).

Source data

Extended Data Fig. 5 SPR binding table and kinetics, binding assay, ligand adsorption, and Notch surface expression.

a, The table shows the affinity constant values for the interaction between DLL4 variants and Notch receptors, and the fold-enhancement of DeltaMAX affinity relative to WT DLL4. b, Table showing the association and dissociation constants measure by SPR for the interaction of DLL4 variants to Notch1 EGF6-13. Half-lives were calculated for the complex DLL4:Notch in each case. SPR measurements were determined at 200 nM concentration of DLL4 proteins. c, Binding assay of WT DLL4 and DeltaMAX tetramers to Notch1-overexpressing CHO-K1 N1-Gal4 cells was measured by flow cytometry. Data represent mean values ± s.d. of three biological replicates. d, The level of Notch1 expression on the surface of cell lines used in this study was determined by flow cytometry. Data represent mean values ± s.d. of three biological replicates. e, Determination of plate adsorption for WT DLL4 and DeltaMAX by ELISA. Data represent mean values ± s.d. of three biological replicates. f, Percentage of CD8+ T cells expressing Notch1 (left graph) and Notch2 (right graph) on cell surface determined by flow cytometry after stimulation with K32-WT DLL4, K32-DeltaMAX, or K32 for 96 hours. Data represent mean values ± s.e.m. of three biological replicates. DeltaMAX statistics are referred to WT DLL4. Statistics were determined with two-way ANOVA.

Extended Data Fig. 6 Fluorescent and luminescent Notch reporter cell lines.

Cartoon schematics describing the fluorescent (a) and luminescent (b) Notch-Gal4 reporter systems used for signaling assays. Flow cytometry dot plots depict the staining of each cell line with Notch-specific antibodies to detect surface expression. HD, heterodimerization domain, NRR, negative regulatory region.

Extended Data Fig. 7 Gating strategy implemented in signaling assays using immobilized ligands, and validation of DLL4-expressing cell lines.

a, DLL4 variants were nonspecifically adsorbed to 96-well tissue culture plates or immobilized to streptavidin plates. Next, Notch1 reporter cells (CHO-K1 N1-Gal4) were added to plates and Notch activation was measured by flow cytometry. The gating strategy to quantify Notch1 activation based on expression of H2B-mCitrine is shown. b, HEK293T cells were transduced to generate stable cell lines expressing WT DLL4 or DeltaMAX and sorted to normalize the expression levels of each ligand. Expression of WT DLL4 and DeltaMAX on HEK293T cells was analyzed by flow cytometry following staining with anti-hDLL4 PE-conjugated antibody. The ligand-expressing cell lines were used for coculture signaling assays with Notch1, Notch2, and Notch3-U2OS luciferase reporter cells. Density plots are representative of three biological replicates.

Extended Data Fig. 8 Optimization of different ligand-presentation strategies.

a, Cartoon representation of different ligand-presentation formats. b, Yeast expressing DeltaMAX (N-EGF5) were cocultured with reporter cells for 24 h at different ratios and fluorescence was measured by flow cytometry. c, HEK293T cells expressing DeltaMAX were cocultured with reporter cells at various ratios for 24 h and Notch activation was measured by flow cytometry. d, Magnetic beads were pre-coated with biotinylated DeltaMAX and cocultured with reporter cells at ratios of 1:20 or 1:40 to stimulate Notch activation. e, SA-polystyrene beads were coated with biotinylated WT DLL4 or DeltaMAX and incubated in ratio 1:1 with CHO-K1 N1-Gal4 reporter cells to measure Notch activation by flow cytometry. f, Flow cytometry dot plots depict the expression level of Notch1 and DeltaMAX. Data in (b), (c), (d) and (e) represent mean values ± s.d. of three biological replicates, while (f) are density plots representative of three biological replicates. DeltaMAX statistics are referred to WT DLL4 or controls. Statistics were determined by two-way ANOVA.

Extended Data Fig. 9 Coculture inhibition of Notch1 using DAPT or DeltaMAX.

a, Dose-titration assay comparing the inhibition potency of DAPT and soluble DeltaMAX. Fluorescent Notch1 reporter cells were cultured in a 1:1 ratio with HEK293T cells stably expressing WT DLL4. Data represent mean values ± s.d. of three biological replicates. b, Summary of the gating strategy used for flow cytometry to differentiate between HEK293T and CHO-K1 N1-Gal4 cell signals. The basal expression of H2B-mCitrine in CHO-K1 N1-Gal4 cells was used as a criterion to distinguish between cell types. Notably, the population identified in the middle and bottom panels (Notch1 reporter CHO-K1 N1-Gal4 cells) corresponds to approximately 50% of the total cells, which is consistent with a 1:1 ratio of reporter cells to 293T cells. Density plots are representative of three biological replicates. DeltaMAX statistics are referred to DAPT. Statistics were determined by two-way ANOVA.

Extended Data Fig. 10 Expression of Notch ligands in stable cell lines.

Stable HEK293T cell lines expressing WT DLL4, DLL1, JAG1, or JAG2 were stained with specific antibodies targeting the ECDs of each Notch ligand and measured by flow cytometry. The expression of Notch ligands, as well as sequencing results, validated these stable cell lines. Flow charts are representative of three biological replicates.

Supplementary information

Source data

Source Data Fig. 3

Unprocessed western blot repeats.

Source Data Fig. 5

Unprocessed western blot repeats.

Source Data Extended Data Fig. 4

Uncropped protein gels.

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Gonzalez-Perez, D., Das, S., Antfolk, D. et al. Affinity-matured DLL4 ligands as broad-spectrum modulators of Notch signaling. Nat Chem Biol 19, 9–17 (2023). https://doi.org/10.1038/s41589-022-01113-4

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