Literature DB >> 31498315

Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation.

Emily A Brown1, Steven C Neier2, Claudia Neuhauser3, Adam G Schrum4, Stephen E P Smith5.   

Abstract

Dynamic protein-protein interactions control cellular behavior, from motility to DNA replication to signal transduction. However, monitoring dynamic interactions among multiple proteins in a protein interaction network is technically difficult. Here, we present a protocol for Quantitative Multiplex Immunoprecipitation (QMI), which allows quantitative assessment of fold changes in protein interactions based on relative fluorescence measurements of Proteins in Shared Complexes detected by Exposed Surface epitopes (PiSCES). In QMI, protein complexes from cell lysates are immunoprecipitated onto microspheres, and then probed with a labeled antibody for a different protein in order to quantify the abundance of PiSCES. Immunoprecipitation antibodies are conjugated to different MagBead spectral regions, which allows a flow cytometer to differentiate multiple parallel immunoprecipitations and simultaneously quantify the amount of probe antibody associated with each. QMI does not require genetic tagging and can be performed using minimal biomaterial compared to other immunoprecipitation methods. QMI can be adapted for any defined group of interacting proteins, and has thus far been used to characterize signaling networks in T cells and neuronal glutamate synapses. Results have led to new hypothesis generation with potential diagnostic and therapeutic applications. This protocol includes instructions to perform QMI, from the initial antibody panel selection through to running assays and analyzing data. The initial assembly of a QMI assay involves screening antibodies to generate a panel, and empirically determining an appropriate lysis buffer. The subsequent reagent preparation includes covalently coupling immunoprecipitation antibodies to MagBeads, and biotinylating probe antibodies so they can be labeled by a streptavidin-conjugated fluorophore. To run the assay, lysate is mixed with MagBeads overnight, and then beads are divided and incubated with different probe antibodies, and then a fluorophore label, and read by flow cytometry. Two statistical tests are performed to identify PiSCES that differ significantly between experimental conditions, and results are visualized using heatmaps or node-edge diagrams.

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Year:  2019        PMID: 31498315      PMCID: PMC8195492          DOI: 10.3791/60029

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  20 in total

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Journal:  Nat Rev Mol Cell Biol       Date:  2007-07       Impact factor: 94.444

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Journal:  Mol Pharmacol       Date:  2015-07-16       Impact factor: 4.436

5.  Physical and functional bivalency observed among TCR/CD3 complexes isolated from primary T cells.

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Journal:  J Immunol       Date:  2011-06-10       Impact factor: 5.422

6.  Signalling protein complexes isolated from primary human skin-resident T cells can be analysed by Multiplex IP-FCM.

Authors:  Stephen E P Smith; Steven C Neier; Tessa R Davis; Mark R Pittelkow; Diana Gil; Adam G Schrum
Journal:  Exp Dermatol       Date:  2014-04       Impact factor: 3.960

7.  A theoretical framework for specificity in cell signaling.

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Journal:  Mol Syst Biol       Date:  2005-10-18       Impact factor: 11.429

8.  Clustering the autisms using glutamate synapse protein interaction networks from cortical and hippocampal tissue of seven mouse models.

Authors:  Emily A Brown; Jonathan D Lautz; Tessa R Davis; Edward P Gniffke; Alison A W VanSchoiack; Steven C Neier; Noah Tashbook; Chiara Nicolini; Margaret Fahnestock; Adam G Schrum; Stephen E P Smith
Journal:  Mol Autism       Date:  2018-09-15       Impact factor: 7.509

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Authors:  L J Bugaj; A J Sabnis; A Mitchell; J E Garbarino; J E Toettcher; T G Bivona; W A Lim
Journal:  Science       Date:  2018-08-31       Impact factor: 47.728

10.  Robustness and Specificity in Signal Transduction via Physiologic Protein Interaction Networks.

Authors:  Adam G Schrum; Diana Gil
Journal:  Clin Exp Pharmacol       Date:  2012-12-21
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