HATRIC-based identification of receptors for orphan ligands
Cellular responses depend on the interactions of extracellular ligands, such as nutrients, growth factors, or drugs, with specific cell-surface receptors. The sensitivity of these interactions to non-physiological conditions, however, makes them challenging to study using in vitro assays. Here we pr...
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Published in | Nature communications Vol. 9; no. 1; pp. 1519 - 8 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
17.04.2018
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
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Summary: | Cellular responses depend on the interactions of extracellular ligands, such as nutrients, growth factors, or drugs, with specific cell-surface receptors. The sensitivity of these interactions to non-physiological conditions, however, makes them challenging to study using in vitro assays. Here we present HATRIC-based ligand receptor capture (HATRIC-LRC), a chemoproteomic technology that successfully identifies target receptors for orphan ligands on living cells ranging from small molecules to intact viruses. HATRIC-LRC combines a click chemistry-based, protein-centric workflow with a water-soluble catalyst to capture ligand-receptor interactions at physiological pH from as few as 1 million cells. We show HATRIC-LRC utility for general antibody target validation within the native nanoscale organization of the surfaceome, as well as receptor identification for a small molecule ligand. HATRIC-LRC further enables the identification of complex extracellular interactomes, such as the host receptor panel for influenza A virus (IAV), the causative agent of the common flu.
Technologies for identifying receptor-ligand pairs on living cells at physiological conditions remain scarce. Here, the authors develop a mass spectrometry-based ligand receptor capture technology that can identify receptors for a diverse range of ligands at physiological pH with as few as a million cells. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-018-03936-z |