» Articles » PMID: 24045637

Protein Synthesis Rate is the Predominant Regulator of Protein Expression During Differentiation

Overview
Journal Mol Syst Biol
Specialty Molecular Biology
Date 2013 Sep 19
PMID 24045637
Citations 115
Authors
Affiliations
Soon will be listed here.
Abstract

External perturbations, by forcing cells to adapt to a new environment, often elicit large-scale changes in gene expression resulting in an altered proteome that improves the cell's fitness in the new conditions. Steady-state levels of a proteome depend on transcription, the levels of transcripts, translation and protein degradation but system-level contribution that each of these processes make to the final protein expression change has yet to be explored. We therefore applied a systems biology approach to characterize the regulation of protein expression during cellular differentiation using quantitative proteomics. As a general rule, it seems that protein expression during cellular differentiation is largely controlled by changes in the relative synthesis rate, whereas the relative degradation rate of the majority of proteins stays constant. In these data, we also observe that the proteins in defined sub-structures of larger protein complexes tend to have highly correlated synthesis and degradation rates but that this does not necessarily extend to the holo-complex. Finally, we provide strong evidence that the generally poor correlation observed between transcript and protein levels can fully be explained once the protein synthesis and degradation rates are taken into account.

Citing Articles

Post-transcriptional regulation in early cell fate commitment of germ layers.

Gomes-Junior R, Delai da Silva Horinouchi C, Hansel-Frose A, Ribeiro A, Pereira I, Spangenberg L BMC Genomics. 2025; 26(1):225.

PMID: 40055639 PMC: 11889779. DOI: 10.1186/s12864-025-11400-8.


Protein degradation and growth dependent dilution substantially shape mammalian proteomes.

Leduc A, Slavov N bioRxiv. 2025; .

PMID: 39990504 PMC: 11844506. DOI: 10.1101/2025.02.10.637566.


Similar, but not the same: multiomics comparison of human valve interstitial cells and osteoblast osteogenic differentiation expanded with an estimation of data-dependent and data-independent PASEF proteomics.

Lobov A, Kuchur P, Boyarskaya N, Perepletchikova D, Taraskin I, Ivashkin A Gigascience. 2025; 14.

PMID: 39798943 PMC: 11724719. DOI: 10.1093/gigascience/giae110.


A promoter-RBS library for fine-tuning gene expression in .

Zhu P, Molina Resendiz M, von Ossowski I, Scheller S Appl Environ Microbiol. 2024; 90(9):e0109224.

PMID: 39132998 PMC: 11409679. DOI: 10.1128/aem.01092-24.


Mitogen signaling strength and duration can control cell cycle decisions.

Nussinov R, Zhang W, Liu Y, Jang H Sci Adv. 2024; 10(27):eadm9211.

PMID: 38968359 PMC: 11809619. DOI: 10.1126/sciadv.adm9211.


References
1.
Fournier M, Paulson A, Pavelka N, Mosley A, Gaudenz K, Bradford W . Delayed correlation of mRNA and protein expression in rapamycin-treated cells and a role for Ggc1 in cellular sensitivity to rapamycin. Mol Cell Proteomics. 2009; 9(2):271-84. PMC: 2830839. DOI: 10.1074/mcp.M900415-MCP200. View

2.
Larance M, Ahmad Y, Kirkwood K, Ly T, Lamond A . Global subcellular characterization of protein degradation using quantitative proteomics. Mol Cell Proteomics. 2012; 12(3):638-50. PMC: 3591657. DOI: 10.1074/mcp.M112.024547. View

3.
Lundberg E, Fagerberg L, Klevebring D, Matic I, Geiger T, Cox J . Defining the transcriptome and proteome in three functionally different human cell lines. Mol Syst Biol. 2010; 6:450. PMC: 3018165. DOI: 10.1038/msb.2010.106. View

4.
Kristensen A, Gsponer J, Foster L . A high-throughput approach for measuring temporal changes in the interactome. Nat Methods. 2012; 9(9):907-9. PMC: 3954081. DOI: 10.1038/nmeth.2131. View

5.
Komatsu M, Waguri S, Chiba T, Murata S, Iwata J, Tanida I . Loss of autophagy in the central nervous system causes neurodegeneration in mice. Nature. 2006; 441(7095):880-4. DOI: 10.1038/nature04723. View