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Time-series transcriptomics and proteomics reveal alternative modes to decode p53 oscillations
Alba Jiménez1, Dan Lu1, Marian Kalocsay1,2
1Department of Systems Biology, Blavatnik Institute at Harvard Medical School, Boston, MA, USA.
Molecular Systems Biology
|March 14, 2022
Summary
Understanding how the p53 protein
Area of Science:
- Molecular Biology
- Cell Biology
- Systems Biology
Background:
- The transcription factor p53 is crucial for cellular responses to stress.
- p53's dynamic behavior (changes in levels over time) influences gene expression.
- Mechanisms linking p53 dynamics to target gene output are not fully understood.
Purpose of the Study:
- To investigate how different p53 dynamics (oscillatory vs. rising) affect target mRNA and protein expression.
- To identify mechanisms decoding p53 dynamics into specific gene expression patterns.
- To understand how these mechanisms contribute to cellular outcomes like proliferation arrest.
Main Methods:
- Systematic quantification of p53 target mRNA and protein levels over time.
- Application of RNA-sequencing and TMT mass spectrometry.
- Mathematical modeling of experimental data.
Main Results:
- Oscillatory p53 dynamics enabled a wider range of mRNA and protein expression patterns.
- Three distinct decoding mechanisms were identified, operating at transcriptional and post-transcriptional levels.
- Rising p53 dynamics led to higher protein induction, promoting proliferation arrest.
Conclusions:
- Cells utilize diverse mechanisms to interpret complex p53 dynamics.
- Specific combinations of decoding mechanisms dictate protein induction under different p53 dynamic states.
- p53 dynamics play a critical role in regulating gene expression and cellular fate.
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