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Deciphering intercellular signaling complexes by interaction-guided chemical proteomics

ABSTRACT: Indirect cell-cell interactions mediated by secreted proteins and their plasma membrane receptors play essential roles for regulating intercellular signaling. However, systematic profiling of the interactions between living cell surface receptors and secretome from neighboring cells remains challenging. Here we developed a chemical proteomics approach, termed interaction-guided crosslinking (IGC), to identify ligand-receptor interactions in situ. By introducing glycan-based ligation and click chemistry, the IGC approach via glycan-to-glycan crosslinking successfully captured receptors from as few as 0.1 million living cells using only 10 ng of secreted ligand. The unparalleled sensitivity and selectivity allow systematic crosslinking and identification of ligand-receptor complexes formed between cell secretome and surfaceome in an unbiased and all-to-all manner, leading to the discovery of a novel ligand-receptor interaction between pancreatic cancer cell-secreted urokinase (PLAU) and neuropilin 1 (NRP1) on pancreatic cancer-associated fibroblasts. This approach is thus useful for systematic exploring new ligand-receptor pairs and discovering critical intercellular signaling events.

INSTRUMENT(S): timsTOF Pro, Orbitrap Fusion, Q Exactive HF, Q Exactive

ORGANISM(S): Homo Sapiens (human) Mus Musculus (mouse)

TISSUE(S): Cell Culture

SUBMITTER: Jiangnan Zheng

LAB HEAD: Ruijun Tian

PROVIDER: PXD038018 | Pride | 2023-07-08

REPOSITORIES: Pride

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Project description:This a model from the article: Harmonic oscillator model of the insulin and IGF1 receptors' allosteric binding and activation. Kiselyov VV, Versteyhe S, Gauguin L, De Meyts P. Mol Syst Biol. 2009;5:243. 19225456 , Abstract: The insulin and insulin-like growth factor 1 receptors activate overlapping signalling pathways that are critical for growth, metabolism, survival and longevity. Their mechanism of ligand binding and activation displays complex allosteric properties, which no mathematical model has been able to account for. Modelling these receptors' binding and activation in terms of interactions between the molecular components is problematical due to many unknown biochemical and structural details. Moreover, substantial combinatorial complexity originating from multivalent ligand binding further complicates the problem. On the basis of the available structural and biochemical information, we develop a physically plausible model of the receptor binding and activation, which is based on the concept of a harmonic oscillator. Modelling a network of interactions among all possible receptor intermediaries arising in the context of the model (35, for the insulin receptor) accurately reproduces for the first time all the kinetic properties of the receptor, and provides unique and robust estimates of the kinetic parameters. The harmonic oscillator model may be adaptable for many other dimeric/dimerizing receptor tyrosine kinases, cytokine receptors and G-protein-coupled receptors where ligand crosslinking occurs. This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

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Deciphering intercellular signaling complexes by interaction-guided chemical proteomics

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