Evidence map›Paper›PMID 37450152›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Discovering Protein-Protein Interactions using Co-Fractionation-Mass Spectrometry with Label-Free Quantitation.

Mopelola O Akinlaja, R Greg Stacey, Queenie W T Chan, Leonard J Foster

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Progress toward a comprehensive brain protein interactome.Biochemical Society transactions · 2025
    Review
  2. Review
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

4 authors.

Mopelola O AkinlajaDepartment of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada.
R Greg StaceyMichael Smith Laboratories, Vancouver, BC, Canada.
Queenie W T ChanMichael Smith Laboratories, Vancouver, BC, Canada.
Leonard J FosterDepartment of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada. foster@msl.ubc.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteins generally achieve their functions through interactions with other proteins, so being able to determine which proteins interact with which other proteins underlies much of molecular biology. Co-fractionation (CF) is a mass spectrometry-based method for detecting proteome-wide protein-protein interactions. An attractive feature of CF is that it is not necessary to label or otherwise alter samples. Although we have previously published a widely used protocol for a label-incorporated CF methodology, no published protocols currently exist for the label-free variation. In this chapter, we describe a label-free CF-MS protocol. This protocol takes a minimum of a week, excluding the time for cell/tissue culture. It begins with cell/tissue lysis under non-denaturing conditions, after which intact protein complexes are isolated using size exclusion chromatography (SEC) where they are fractionated according to size. The proteins in each fraction are then prepared for mass spectrometry analysis where the constituent proteins are identified and quantified. Finally, we describe an in-house bioinformatics pipeline, PrInCE, to accurately predict protein complexes. Taken together, co-fractionation methodologies combined with mass spectrometry can identify and quantify thousands of protein-protein interactions in biological systems.

Indexed as

ProteomeChromatography, GelMass SpectrometryProteomeCo-fractionationLabel-free quantitationMass spectrometryProtein–protein interactionsSize exclusion chromatography

Identifiers

PMID37450152

What OpenQuestion holds

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Registered trials

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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.