Label-free Quantitative Analysis of Protein Expression Alterations in miR-26a-Knockout HeLa Cells using SWATH-MS Technology View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Hexiao Shen, Li Li, Zhaowei Teng, Tianqing Meng, Xiangbin Kong, Yan Hu, Yun Zhu, Lixin Ma

ABSTRACT

MicroRNAs (miRNAs) bind to the 3'-untranslated region of target mRNAs in a sequence-specific manner and subsequently repress gene translation. Human miR-26a has been studied extensively, but the target transcripts are far from complete. We first employed the CRISPR-Cas9 system to generate an miR-26a-knockout line in human cervical cancer HeLa cells. The miR26a-knockout line showed increased cell growth and altered proliferation. Proteomics technology of sequential window acquisition of all theoretical mass spectra (SWATH-MS) was utilized to compare the protein abundance between the wild-type and the knockout lines, with an attempt to identify transcripts whose translation was influenced by miR-26a. Functional classification of the proteins with significant changes revealed their function in stress response, proliferation, localization, development, signaling, etc. Several proteins in the cell cycle/proliferation signaling pathway were chosen to be validated by western blot and parallel reaction monitoring (PRM). The satisfactory consistency among the three approaches indicated the reliability of the SWATH-MS quantification. Among the computationally predicted targets, a subset of the targets was directly regulated by miR-26a, as demonstrated by luciferase assays and Western blotting. This study creates an inventory of miR-26a-targeted transcripts in HeLa cells and provides fundamental knowledge to further explore the functions of miR-26a in human cancer. More... »

PAGES

1399

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-018-34904-8

DOI

http://dx.doi.org/10.1038/s41598-018-34904-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111911872

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30718521


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