Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Physician-Scientist Development
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • In-Press Preview
    • Resource and Technical Advances
    • Clinical Research and Public Health
    • Research Letters
    • Editorials
    • Perspectives
    • Physician-Scientist Development
    • Reviews
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Resource and Technical Advances
  • Clinical Research and Public Health
  • Research Letters
  • Editorials
  • Perspectives
  • Physician-Scientist Development
  • Reviews
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
Single-cell profiling reveals GPCR heterogeneity and functional patterning during neuroinflammation
Denise Tischner, Myriam Grimm, Harmandeep Kaur, Daniel Staudenraus, Jorge Carvalho, Mario Looso, Stefan Günther, Florian Wanke, Sonja Moos, Nelly Siller, Johanna Breuer, Nicholas Schwab, Frauke Zipp, Ari Waisman, Florian C. Kurschus, Stefan Offermanns, Nina Wettschureck
Denise Tischner, Myriam Grimm, Harmandeep Kaur, Daniel Staudenraus, Jorge Carvalho, Mario Looso, Stefan Günther, Florian Wanke, Sonja Moos, Nelly Siller, Johanna Breuer, Nicholas Schwab, Frauke Zipp, Ari Waisman, Florian C. Kurschus, Stefan Offermanns, Nina Wettschureck
View: Text | PDF
Research Article Immunology

Single-cell profiling reveals GPCR heterogeneity and functional patterning during neuroinflammation

  • Text
  • PDF
Abstract

GPCR expression was intensively studied in bulk cDNA of leukocyte populations, but limited data are available with respect to expression in individual cells. Here, we show a microfluidic-based single-cell GPCR expression analysis in primary T cells, myeloid cells, and endothelial cells under naive conditions and during experimental autoimmune encephalomyelitis, the mouse model of multiple sclerosis. We found that neuroinflammation induces characteristic changes in GPCR heterogeneity and patterning, and we identify various functionally relevant subgroups with specific GPCR profiles among spinal cord–infiltrating CD4 T cells, macrophages, microglia, or endothelial cells. Using GPCRs CXCR4, S1P1, and LPHN2 as examples, we show how this information can be used to develop new strategies for the functional modulation of Th17 cells and activated endothelial cells. Taken together, single-cell GPCR expression analysis identifies functionally relevant subpopulations with specific GPCR repertoires and provides a basis for the development of new therapeutic strategies in immune disorders.

Authors

Denise Tischner, Myriam Grimm, Harmandeep Kaur, Daniel Staudenraus, Jorge Carvalho, Mario Looso, Stefan Günther, Florian Wanke, Sonja Moos, Nelly Siller, Johanna Breuer, Nicholas Schwab, Frauke Zipp, Ari Waisman, Florian C. Kurschus, Stefan Offermanns, Nina Wettschureck

×

Figure 2

Single-cell GPCR expression in CD4 T cells after MOG35-55-dependent activation in vivo or in vitro.

Options: View larger image (or click on image) Download as PowerPoint
Single-cell GPCR expression in CD4 T cells after MOG35-55-dependent acti...
(A) Heat map of GPCR expression in CD4ln, CD4dr, and CD4sc (50, 43, 115 cells from 3, 3, 12 mice, respectively); horizontal bars on the right side visualize expression frequency (%). (B) Number of GPCRs expressed in individual CD4ln, CD4dr, CD4sc. (C) Number of GPCRs expressed in individual splenic CD4 cells (CD4spn) from 2D2 TCR transgenic mice in the naive state or after in vitro differentiation toward Th1 or Th17, respectively. (D) T-SNE plot showing the degree of similarity between individual in vitro–differentiated (Th1, 26 cells; Th17, 43 cells) and in vivo–differentiated CD4 T cells. The closer together cells are plotted, the more similar they are; k-means cluster assignment is indicated by color; cell type is indicated by symbols. Expression data are calculated as 2(Lod Ct – sample Ct); LoD Ct was set to 24. ***P < 0.001 (B, C) by unpaired t test.

Copyright © 2026 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts