Letter | Published:

Monitoring T cell–dendritic cell interactions in vivo by intercellular enzymatic labelling

Nature volume 553, pages 496500 (25 January 2018) | Download Citation

Abstract

Interactions between different cell types are essential for multiple biological processes, including immunity, embryonic development and neuronal signalling. Although the dynamics of cell–cell interactions can be monitored in vivo by intravital microscopy1, this approach does not provide any information on the receptors and ligands involved or enable the isolation of interacting cells for downstream analysis. Here we describe a complementary approach that uses bacterial sortase A-mediated cell labelling across synapses of immune cells to identify receptor–ligand interactions between cells in living mice, by generating a signal that can subsequently be detected ex vivo by flow cytometry. We call this approach for the labelling of ‘kiss-and-run’ interactions between immune cells ‘Labelling Immune Partnerships by SorTagging Intercellular Contacts’ (LIPSTIC). Using LIPSTIC, we show that interactions between dendritic cells and CD4+ T cells during T-cell priming in vivo occur in two distinct modalities: an early, cognate stage, during which CD40–CD40L interactions occur specifically between T cells and antigen-loaded dendritic cells; and a later, non-cognate stage during which these interactions no longer require prior engagement of the T-cell receptor. Therefore, LIPSTIC enables the direct measurement of dynamic cell–cell interactions both in vitro and in vivo. Given its flexibility for use with different receptor–ligand pairs and a range of detectable labels, we expect that this approach will be of use to any field of biology requiring quantification of intercellular communication.

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Acknowledgements

We thank H. Ploegh for introducing us to sortase A; H. Yang, S. Markoulaki and R. Jaenisch for generating gene-targeted mice; A. Ting for NLG- and NRX-expressing constructs; and L. Mesin and C. F. Opel for technical advice. This work was funded by NIH grants DP5OD012146 and R01AI119006 to G.D.V. and a Starr Cancer Consortium grant to G.D.V. and N.H. G.P. was supported by the Swiss National Science Foundation Postdoctoral fellowship and the Cancer Research Institute Irvington Postdoctoral fellowship. G.V. is a Searle Scholar.

Author information

Affiliations

  1. Laboratory of Lymphocyte Dynamics, The Rockefeller University, 1230 York Avenue, New York, New York, USA

    • Giulia Pasqual
    • , Aleksey Chudnovskiy
    • , Jeroen M. J. Tas
    • , Marianna Agudelo
    •  & Gabriel D. Victora
  2. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    • Lawrence D. Schweitzer
    • , Ang Cui
    •  & Nir Hacohen
  3. Center for Cancer Research, Massachusetts General Hospital, Department of Medicine, Boston, Massachusetts, USA

    • Lawrence D. Schweitzer
    • , Ang Cui
    •  & Nir Hacohen

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Contributions

G.P. and G.D.V. conceived the study, designed and analysed experiments and wrote the manuscript. G.P. performed all experimental work (with the exception of gene-expression analysis), with sporadic assistance from A.Ch., J.M.T. and M.A. L.D.S., A.Cu. and N.H. contributed the gene-expression profiling work, including experiments and data analysis presented in Fig. 4g and Extended Data Fig. 10 and wrote the text for these experiments.

Competing interests

G.P. and G.D.V. have submitted a US Non Provisional Patent Application for the LIPSTIC technology (US20160097773).

Corresponding author

Correspondence to Gabriel D. Victora.

Reviewer Information Nature thanks M. Dustin, A. Esser-Kahn, T. Mempel and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Supplementary information

PDF files

  1. 1.

    Life Sciences Reporting Summary

    DESCRIPTION

Excel files

  1. 1.

    Supplementary Table 1

    Differentially expressed genes between biotin+ and biotin- DC populations. This table contains a list of differentially expressed genes (log2 fold change > 1 and FDR < 0.05, see Methods section) and GSEA analysis showing selected top gene sets obtained by GO enrichment analysis with FDR indicated. Data are derived from a single experiment, n=3.

  2. 2.

    Supplementary Table 2

    This table contains the DNA sequences of the plasmids used in the study.

  3. 3.

    Supplementary Table 3

    This table contains a list of antibodies used in the study.

Videos

  1. 1.

    Imaging of LIPSTIC labeling between lymphocytes in vitro

    Lymphocytes were imaged as described in Extended Data Fig. 3a. The video (675X speed, total real time 90 min) shows transfer of AlexaFluor647-SELPETGG (white) from CD40L-SrtA+ T cells (green) to G5-CD40+ B cells (red) upon interaction.

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DOI

https://doi.org/10.1038/nature25442

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