Identification of Novel MAGE-G1-Interacting Partners in Retinoic Acid-Induced P19 Neuronal Differentiation Using SILAC-Based Proteomics.

Yong Liu, Yujian Chen, Shide Lin, Shuguang Yang, Shaojun Liu

Open access · goldAbstract read

In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

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0citing papers in PubMed

0.2field-weighted citation impact, top 48% 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

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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

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0 citing papers in PubMed, 2 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Yong LiuState Key Laboratory of Proteomics, Department of Neurobiology, Institute of Basic Medical Sciences, Beijing, 100850, China.

Yujian ChenState Key Laboratory of Proteomics, Department of Neurobiology, Institute of Basic Medical Sciences, Beijing, 100850, China.

Shide LinState Key Laboratory of Proteomics, Department of Neurobiology, Institute of Basic Medical Sciences, Beijing, 100850, China.

Shuguang YangState Key Laboratory of Proteomics, Department of Neurobiology, Institute of Basic Medical Sciences, Beijing, 100850, China.

Shaojun LiuState Key Laboratory of Proteomics, Department of Neurobiology, Institute of Basic Medical Sciences, Beijing, 100850, China.

Beijing Proteome Research Center · CNInstitute of Basic Medical Sciences of the Chinese Academy of Medical Sciences

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MAGE-G1 is a protein plays role in the early process of neurogenesis. However, the fundamental roles MAGE-G1 played in neurogenesis have not yet been completely understood. Finding the partners MAGE-G1 interacting with will surely contribute to the function study of MAGE-G1. In this study, using Stable Isotope Labeling by Amino acids in Cell culture-immunoprecipitation quantitative proteomics, we screened the interacting proteins of MAGE-G1 during retinoic acid -induced neuronal differentiation of P19 cells and firstly found that FSCN1 and VIME were potential novel MAGE-G1-interacting proteins. Then, the interaction between overexpressed MAGE-G1 and FSCN1 or VIME was validated by GST-pull down assay in bacteria and by co-immunoprecipitation assay in COS7 cells. Endogenous co-immunoprecipitation assay further confirmed that MAGE-G1 interacted with FSCN1 or VIME in P19 cells after a 6-day retinoic acid-induced neuronal differentiation. Those results provide a functional linkage between MAGE-G1 and FSCN1 or VIME and may facilitate a better understanding of the fundamental aspects of MAGE-G1 during neurogenesis.

Indexed as

Gene Expression Regulation, NeoplasticAmino Acid SequenceAnimalsCell DifferentiationCell Line, TumorChlorocebus aethiopsCOS CellsGlutathione TransferaseIsotope LabelingMelanoma-Specific AntigensMiceMicrofilament ProteinsNeoplastic Stem CellsNeurogenesisNeuronsProtein BindingGlutathione TransferaseMelanoma-Specific AntigensMicrofilament ProteinsOlfr73 protein, mouseReceptors, OdorantRecombinant Fusion ProteinsTretinoinVimentinVim protein, mouse

Identifiers

PMID28374796

DOI10.1038/srep44699

PMCPMC5379670

OpenAlexW2604692236

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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.