Direct identification of ligand-receptor interactions on living cells and tissues

Journal name:
Nature Biotechnology
Volume:
30,
Pages:
997–1001
Year published:
DOI:
doi:10.1038/nbt.2354
Received
Accepted
Published online

Many cellular responses are triggered by proteins, drugs or pathogens binding to cell-surface receptors, but it can be challenging to identify which receptors are bound by a given ligand. Here we describe TRICEPS, a chemoproteomic reagent with three moieties—one that binds ligands containing an amino group, a second that binds glycosylated receptors on living cells and a biotin tag for purifying the receptor peptides for identification by quantitative mass spectrometry. We validated this ligand-based, receptor-capture (LRC) technology using insulin, transferrin, apelin, epidermal growth factor, the therapeutic antibody trastuzumab and two DARPins targeting ErbB2. In some cases, we could also determine the approximate ligand-binding sites on the receptors. Using TRICEPS to label intact mature vaccinia viruses, we identified the cell surface proteins AXL, M6PR, DAG1, CSPG4 and CDH13 as binding factors on human cells. This technology enables the identification of receptors for many types of ligands under near-physiological conditions and without the need for genetic manipulations.

At a glance

Figures

  1. TRICEPS enables LRC.
    Figure 1: TRICEPS enables LRC.

    (a) TRICEPS consists of an N-hydroxysuccinimide ester for the coupling to ligands via primary amines, a trifluoroacetyl-protected hydrazine moiety for the subsequent capture of glycoprotein receptors on living cells via aldehydes introduced into carbohydrates by mild oxidation and a biotin moiety for the affinity purification of captured glycopeptides. Flexibility is provided by the stochastic coupling of TRICEPS to topologically different sites on ligands, the long (~48 Å) and flexible spacer between the reactive moieties and the presence of typically more than one aldehyde in a single carbohydrate structure after mild oxidation. Alternative ligand-reactive functionalities may be implemented to further broaden the possible application (e.g., for small-molecule ligands). (b) Labeling of living cells with TRICEPS through the aldehyde-reactive functionality. Commercially available biocytin hydrazide (an unprotected aldehyde-reactive biotin derivative) was used as a reference. Amine-reactive moieties of TRICEPS were quenched with glycine and reagents were reacted with Jurkat T lymphocytes with or without prior oxidation of the cells with sodium metaperiodate. Biotinylation was detected by flow cytometric analysis of ungated cell populations after staining with streptavidin-FITC.

  2. Workflow for the LRC and identification on living cells.
    Figure 2: Workflow for the LRC and identification on living cells.

    (i) Conjugation of a purified ligand of interest to TRICEPS and quenching of an equimolar amount of TRICEPS with glycine (or coupling to a control ligand with known or no binding preferences) in the control reaction. (ii) Mild periodate oxidation of target cells or tissue to introduce aldehydes into carbohydrate structures for TRICEPS capture. (iii) LRC and stochastic biotinylation of random cell surface glycoproteins according to their abundance. (iv) Cell lysis and tryptic digest of proteins. (v) Biotin-mediated affinity enrichment of captured glycopeptides on streptavidin beads. (vi) Cell surface N-glycopeptide release by PNGase F treatment, which introduces the N[115]-X-S/T motif (N[115], deamidated asparagine; X, any amino acid except proline; S/T, serine or threonine, respectively) in formerly N-glycosylated peptides. (vii) Glycopeptide identification by high mass accuracy MS and peptide filtering for the presence of the N[115]-X-S/T motif. (viii) Relative label-free quantification of formerly glycosylated cell surface peptides to identify specific LRC events.

  3. LRC identifies receptors and receptor panels for ligands ranging from peptides to intact viruses on living cells and tissues.
    Figure 3: LRC identifies receptors and receptor panels for ligands ranging from peptides to intact viruses on living cells and tissues.

    (a) LRC with human insulin on differentiated murine visceral adipocytes. Data are shown on the peptide level. (b) LRC with transferrin and apelin on U-2 OS cells. Data are shown on the protein level. Two glycopeptides of transferrin were captured and identified as well without prior exposure of the ligand to oxidative conditions, which was also observed with other glycoprotein ligands used later on. APLNR, apelin receptor; TF, transferrin; TFRC, transferrin receptor. (c) LRC with epidermal growth factor and trastuzumab on U251 cells in biological triplicates. The receptor candidate space highlighted in gray is defined by an enrichment factor of fourfold or greater and an FDR-adjusted P-value less than or equal to 0.01. IGHG1, immunoglobulin heavy constant gamma 1. (d) LRC with DARPins on BT-474 cells in biological triplicates. Data are shown on the glycosylation site level. Identified ErbB2 glycosylation sites: Asn124, Asn187 (ErbB2 domain I), Asn629 (ErbB2 domain IV). (e) LRC with trastuzumab on primary breast cancer tissue in technical (multiple LC-MS/MS runs of the same sample) triplicates. (f) LRC with intact vaccinia viruses on HeLa CCL2 cells in biological triplicates. Receptor candidates with a fold enrichment ≥4 and a P value ≤ 0.05 were tested for effects on viral infectivity in follow-up investigations. Identified peptides and proteins are shown in gray. Ligands, receptors and receptor candidates are shown in black. (g) Representative images of siRNA-treated HeLa cells infected with vaccinia virus (red, nuclei; green, vaccinia virus early protein expression). (h) Percentage of vaccinia virus–infected HeLa cells after siRNA knockdown of the receptor candidates identified in the LRC experiment with intact viruses. Infection rates were calculated relative to control cells transfected with AllStars Negative Control siRNAs (All*Neg). Error bars indicate s.d.

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Author information

  1. These authors contributed equally to this work.

    • Ock-Youm Jeon &
    • Samuel Kilcher

Affiliations

  1. Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Switzerland.

    • Andreas P Frei,
    • Hansjoerg Moest,
    • Lisa M Henning,
    • Ruedi Aebersold &
    • Bernd Wollscheid
  2. NCCR Neuro Center for Proteomics, University of Zurich, Switzerland.

    • Andreas P Frei,
    • Hansjoerg Moest,
    • Lisa M Henning &
    • Bernd Wollscheid
  3. PhD Program in Molecular Life Sciences (MLS), University of Zurich/ETH Zurich, Switzerland.

    • Andreas P Frei,
    • Samuel Kilcher &
    • Christian Jost
  4. Department of Chemistry and Applied Biosciences, Laboratory of Organic Chemistry, ETH Zurich, Switzerland.

    • Ock-Youm Jeon &
    • Erick M Carreira
  5. Department of Biology, Institute of Biochemistry, ETH Zurich, Switzerland.

    • Samuel Kilcher &
    • Jason Mercer
  6. Department of Health and Technology, Institute of Food, Nutrition and Health, ETH Zurich, Switzerland.

    • Hansjoerg Moest
  7. Department of Biochemistry, University of Zurich, Switzerland.

    • Christian Jost &
    • Andreas Plückthun
  8. Faculty of Science, University of Zurich, Switzerland.

    • Andreas Plückthun &
    • Ruedi Aebersold
  9. Competence Center for Systems Physiology and Metabolic Diseases, Zurich, Switzerland.

    • Ruedi Aebersold

Contributions

A.P.F. and B.W. designed the project and wrote the paper. A.P.F. performed experiments and analyzed all data. A.P.F., B.W., O.-Y.J. and E.M.C. designed TRICEPS and O.-Y.J. synthesized the reagents. J.M. and S.K. designed and performed vaccinia virus experiments and J.M. edited the manuscript. C.J. and A.P. designed DARPin experiments and performed ELISAs. R.A., H.M. and L.M.H. contributed ideas and performed experiments. All authors discussed the results and implications and commented on the manuscript at all stages.

Competing financial interests

The authors declare no competing financial interests.

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Supplementary information

PDF files

  1. Supplementary Text and Figures (2 MB)

    Supplementary Figures 1–6 and Supplementary Note 1

Excel files

  1. Supplementary Table 1 (61 KB)

    LRC with human insulin on murine adipocytes

  2. Supplementary Table 2 (213 KB)

    LRC competition experiment with human insulin on Jurkat T lymphocytes

  3. Supplementary Table 3 (94 KB)

    LRC with transferrin and apelin on U-2 OS cells

  4. Supplementary Table 4 (57 KB)

    LRC with EGF and trastuzumab on U251 cells

  5. Supplementary Table 5 (53 KB)

    LRC with DARPin 9.01 and DARPin H14 on BT-474 cells

  6. Supplementary Table 6 (213 KB)

    LRC with trastuzumab on primary breast cancer tissue

  7. Supplementary Table 7 (61 KB)

    LRC with vaccinia virus on HeLa CCL2 cells

  8. Supplementary Table 8 (29 KB)

    siRNA sequences used for target protein depletion

Additional data