Evidence map›Paper›PMID 24722732›Full record

ArticleMolecular & cellular proteomics : MCP2014

Controlling for gene expression changes in transcription factor protein networks.

Charles A S Banks, Zachary T Lee, Gina Boanca, Mahadevan Lakshminarasimhan, Brad D Groppe, Zhihui Wen, Gaye L Hattem, Chris W Seidel, Laurence Florens, Michael P Washburn

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

18 citing papers in PubMed, 25 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Charles A S BanksFrom the ‡Stowers Institute for Medical Research, Kansas City, Missouri 64110;
Zachary T LeeFrom the ‡Stowers Institute for Medical Research, Kansas City, Missouri 64110;
Gina BoancaFrom the ‡Stowers Institute for Medical Research, Kansas City, Missouri 64110;
Mahadevan LakshminarasimhanFrom the ‡Stowers Institute for Medical Research, Kansas City, Missouri 64110;
Brad D GroppeFrom the ‡Stowers Institute for Medical Research, Kansas City, Missouri 64110;
Zhihui WenFrom the ‡Stowers Institute for Medical Research, Kansas City, Missouri 64110;
Gaye L HattemFrom the ‡Stowers Institute for Medical Research, Kansas City, Missouri 64110;
Chris W SeidelFrom the ‡Stowers Institute for Medical Research, Kansas City, Missouri 64110;
Laurence FlorensFrom the ‡Stowers Institute for Medical Research, Kansas City, Missouri 64110;
Michael P WashburnFrom the ‡Stowers Institute for Medical Research, Kansas City, Missouri 64110; §Departments of Pathology & Laboratory Medicine, University of Kansas Medical Center, Kansas City, Kansas 66160 mpw@stowers.org.
Stowers Institute for Medical Research · USUniversity of Kansas · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of affinity purification technologies combined with mass spectrometric analysis of purified protein mixtures has been used both to identify new protein-protein interactions and to define the subunit composition of protein complexes. Transcription factor protein interactions, however, have not been systematically analyzed using these approaches. Here, we investigated whether ectopic expression of an affinity tagged transcription factor as bait in affinity purification mass spectrometry experiments perturbs gene expression in cells, resulting in the false positive identification of bait-associated proteins when typical experimental controls are used. Using quantitative proteomics and RNA sequencing, we determined that the increase in the abundance of a set of proteins caused by overexpression of the transcription factor RelA is not sufficient for these proteins to then co-purify non-specifically and be misidentified as bait-associated proteins. Therefore, typical controls should be sufficient, and a number of different baits can be compared with a common set of controls. This is of practical interest when identifying bait interactors from a large number of different baits. As expected, we found several known RelA interactors enriched in our RelA purifications (NFκB1, NFκB2, Rel, RelB, IκBα, IκBβ, and IκBε). We also found several proteins not previously described in association with RelA, including the small mitochondrial chaperone Tim13. Using a variety of biochemical approaches, we further investigated the nature of the association between Tim13 and NFκB family transcription factors. This work therefore provides a conceptual and experimental framework for analyzing transcription factor protein interactions.

Indexed as

ProteomicsCytoplasmGene Expression RegulationHEK293 CellsHumansMass SpectrometryMultiprotein ComplexesProtein Interaction MapsTranscription Factor RelATranscription FactorsMultiprotein ComplexesRELA protein, humanTranscription Factor RelATranscription Factors

Identifiers

PMID24722732
PMCPMC4047470
OpenAlexW2047122698

What OpenQuestion holds

Textmetadata
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.