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Measurement of Protein Turnover Rates in Senescent and Non-Dividing Cultured Cells with Metabolic Labeling and Mass Spectrometry
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Multiple time-series expression trajectories imply dynamic functional changes during cellular senescence.

Ming-Xia Ge1,2,3,4,5, Qin Yu1, Gong-Hua Li1

  • 1State Key Laboratory of Genetic Resources and Evolution/Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China.

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|August 26, 2022
PubMed
Summary
This summary is machine-generated.

Cellular senescence involves dynamic gene expression changes over time. This study identifies four distinct gene expression trajectories in aging human dermal fibroblasts, revealing new insights into senescence regulation.

Keywords:
Cellular senescenceExpression profileTime-series analysisTrajectoryTranscriptome

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Area of Science:

  • Cellular and Molecular Biology
  • Epigenetics and Aging Research

Background:

  • Cellular senescence, a state of irreversible growth arrest, is crucial in aging and disease.
  • While transcriptomic changes in senescent cells are known, their temporal dynamics are poorly understood.

Purpose of the Study:

  • To investigate the dynamic transcriptomic changes during the progression of cellular senescence in human dermal fibroblasts (HDFs).
  • To identify distinct gene expression patterns and their associated biological pathways during senescence.

Main Methods:

  • Time-series transcriptome profiling of HDFs from proliferation to senescence.
  • Analysis of gene expression dynamics to identify temporal trajectories.
  • Pathway enrichment analysis of identified gene sets.

Main Results:

  • Four distinct gene expression trajectories (C1-C4) were identified during senescence progression.
  • Genes showed varied dynamics: continuous up/down-regulation or stable expression until senescence onset.
  • These trajectories were enriched in pathways related to cellular senescence regulation.

Conclusions:

  • Cellular senescence is characterized by complex, non-linear transcriptomic dynamics.
  • The identified trajectories provide a framework for understanding temporal gene regulation in senescence.
  • This study offers novel insights into the dynamic mechanisms governing cellular senescence.