Evidence map›Paper›PMID 22720010›Full record

ArticlePloS one2012

Identification of karyopherin α1 and α7 interacting proteins in porcine tissue.

Ki-Eun Park, H Dorota Inerowicz, Xin Wang, Yanfang Li, Stephanie Koser, Ryan A Cabot

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

4 citing papers in PubMed, 11 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

6 authors at 1 institution in 1 country.

Ki-Eun ParkDepartment of Animal Sciences, Purdue University, West Lafayette, Indiana, United States of America.
H Dorota Inerowicz
Xin Wang
Yanfang Li
Stephanie Koser
Ryan A Cabot
Purdue University West Lafayette · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Specialized trafficking systems in eukaryotic cells serve a critical role in partitioning intracellular proteins between the nucleus and cytoplasm. Cytoplasmic proteins (including chromatin remodeling enzymes and transcription factors) must gain access to the nucleus to exert their functions to properly program fundamental cellular events ranging from cell cycle progression to gene transcription. Knowing that nuclear import mediated by members of the karyopherin α family of transport receptors plays a critical role in regulating development and differentiation, we wanted to determine the identity of proteins that are trafficked by this karyopherin α pathway. To this end, we performed a GST pull-down assay using porcine orthologs of karyopherin α1 (KPNA1) and karyopherin α7 (KPNA7) and prey protein derived from porcine fibroblast cells and used a liquid chromatography and tandem mass spectrometry (LC-MS/MS) approach to determine the identity of KPNA1 and KPNA7 interacting proteins. Our screen revealed that the proteins that interact with KPNA1 and KPNA7 are generally nuclear proteins that possess nuclear localization signals. We further validated two candidate proteins from this screen and showed that they are able to be imported into the nucleus in vivo and also interact with members of the karyopherin α family of proteins in vitro. Our results also reveal the utility of using a GST pull-down approach coupled with LC-MS/MS to screen for protein interaction partners in a non-traditional model system.

Indexed as

alpha KaryopherinsAnimalsChromatography, LiquidFluorescent DyesProtein BindingProteinsSwineTandem Mass Spectrometryalpha KaryopherinsFluorescent DyesProteins

Identifiers

PMID22720010
PMCPMC3374799
OpenAlexW2013313009

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.