4.8 Article

Detection of cell-cell interactions via photocatalytic cell tagging

Journal

NATURE CHEMICAL BIOLOGY
Volume 18, Issue 8, Pages 850-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41589-022-01044-0

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The growing understanding of immune cell-cell interactions has led to the development of immunotherapies. However, characterizing complex cell-cell interfaces in high resolution is challenging. In this study, a technology called photocatalytic cell tagging (PhoTag) is introduced, which uses specific antibodies and a photocatalyst to study cell-cell interactions. The researchers successfully demonstrated selective labeling of the PD-1/PD-L1 axis and observed interactions between different cell types. This technology will contribute to a better understanding of intercellular communication in various biological systems.
The growing appreciation of immune cell-cell interactions within disease environments has led to extensive efforts to develop immunotherapies. However, characterizing complex cell-cell interfaces in high resolution remains challenging. Thus, technologies leveraging therapeutic-based modalities to profile intercellular environments offer opportunities to study cell-cell interactions with molecular-level insight. We introduce photocatalytic cell tagging (PhoTag) for interrogating cell-cell interactions using single-domain antibodies (VHHs) conjugated to photoactivatable flavin-based cofactors. Following irradiation with visible light, the flavin photocatalyst generates phenoxy radical tags for targeted labeling. Using this technology, we demonstrate selective synaptic labeling across the PD-1/PD-L1 axis in antigen-presenting cell-T cell systems. In combination with multiomics single-cell sequencing, we monitored interactions between peripheral blood mononuclear cells and Raji PD-L1 B cells, revealing differences in transient interactions with specific T cell subtypes. The utility of PhoTag in capturing cell-cell interactions will enable detailed profiling of intercellular communication across different biological systems.

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