Evidence map›Paper›PMID 31498315›Full record

ArticleJournal of visualized experiments : JoVE2019

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

Emily A Brown, Steven C Neier, Claudia Neuhauser, Adam G Schrum, Stephen E P Smith

Open access · greenAbstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.5field-weighted citation impact, top 35% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 14 citations in OpenAlex.

  1. The Alzheimer's disease risk gene SORL1 is a regulator of excitatory neuronal function.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 1 country.

Emily A BrownCenter for Integrative Brain Research, Seattle Children's Research Institute; Graduate Program in Neuroscience, University of Washington.
Steven C NeierDepartment of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Department of Medicine, Harvard Medical School; Broad Institute of Harvard and MIT.
Claudia NeuhauserDepartment of Mathematics, University of Houston.
Adam G SchrumDepartment of Molecular Microbiology and Immunology, School of Medicine, University of Missouri; Department of Surgery, School of Medicine, University of Missouri; Department Bioengineering, College of Engineering, University of Missouri.
Stephen E P SmithCenter for Integrative Brain Research, Seattle Children's Research Institute; Graduate Program in Neuroscience, University of Washington; Department of Pediatrics, University of Washington; seps@uw.edu.
University of Washington · USDana-Farber Cancer Institute · USUniversity of Houston · USUniversity of Missouri · US

Funding

Investigating the synaptic pathology of AutismR01MH113545 · NIMH · SEATTLE CHILDREN'S HOSPITAL · PI Stephen Edward Paucha Smith · 2018 to 2026
$5.8M
Protein Interaction Network Analysis to Test the Synaptic Hypothesis of AutismR00MH102244 · NIMH · SEATTLE CHILDREN'S HOSPITAL · PI SMITH, STEPHEN EDWARD PAUCHA · 2015 to 2017
$734k
NIMH NIH HHS R00 MH102244NIMH NIH HHS R01 MH113545
6 · The paper itself

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.

Indexed as

Protein Interaction MapsAntibodiesFlow CytometryHumansImmunoprecipitationMicrospheresNeuronsProteinsSignal TransductionT-LymphocytesAntibodiesProteins

Identifiers

PMID31498315
PMCPMC8195492
OpenAlexW2969978428

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.