Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation

0524081 - ÚMG 2021 RIV US eng J - Journal Article
Šalovská, Barbora - Zhu, H. - Gandhi, T. - Frank, M. - Li, W. - Rosenberger, G. - Wu, Ch. - Germain, P-L. - Zhou, H. - Hodný, Zdeněk - Reiter, L. - Liu, Y.
Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation.
Molecular Systems Biology. Roč. 16, č. 3 (2020), č. článku e9170. ISSN 1744-4292. E-ISSN 1744-4292
Institutional support: RVO:68378050
Keywords : alternative splicing * DIA mass spectrometry * protein turnover * proteomics * pulsed SILAC
OECD category: Cell biology
Impact factor: 11.429, year: 2020
Method of publishing: Open access
https://www.embopress.org/doi/full/10.15252/msb.20199170

Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post-translational turnover, we devised a strategy combining pulse stable isotope-labeled amino acids in cells (pSILAC), data-independent acquisition mass spectrometry (DIA-MS), and a novel data analysis framework that resolves protein degradation rate on the level of mRNA alternative splicing isoforms and isoform groups. We demonstrated our approach by the genome-wide correlation analysis between mRNA amounts and protein degradation across different strains of HeLa cells that harbor a high grade of gene dosage variation. The dataset revealed that specific biological processes, cellular organelles, spatial compartments of organelles, and individual protein isoforms of the same genes could have distinctive degradation rate. The protein degradation diversity thus dissects the corresponding buffering or concerting protein turnover control across cancer cell lines. The data further indicate that specific mRNA splicing events such as intron retention significantly impact the protein abundance levels. Our findings support the tight association between transcriptome variability and proteostasis and provide a methodological foundation for studying functional protein degradation.
Permanent Link: http://hdl.handle.net/11104/0308420