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Probabilistic models of uORF-mediated ATF4 translation control.

Olivia N J M Marasco1, Marc R Roussel1, Nehal Thakor2

  • 1Alberta RNA Research and Training Institute, University of Lethbridge, Canada; Department of Chemistry and Biochemistry, University of Lethbridge, Lethbridge, Alberta, T1K 3M4, Canada.

Mathematical Biosciences
|December 9, 2021
PubMed
Summary
This summary is machine-generated.

This study models how cells increase translation of the ATF4 (activating transcription factor 4) protein during stress, despite overall translation rates decreasing. The models explore the "race to reload" mechanism involving upstream open reading frames.

Keywords:
ATF4Computer algebraDynamic publicationProbabilistic modelTranslation controlUpstream open reading frame

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Area of Science:

  • Molecular Biology
  • Cellular Stress Response
  • Gene Regulation

Background:

  • Activating transcription factor 4 (ATF4) is crucial for cellular stress response.
  • ATF4 mRNA levels are constant, but its translation increases during stress.
  • Global translation decreases during cellular stress, creating a regulatory challenge.

Purpose of the Study:

  • To model the regulatory system controlling ATF4 translation during cellular stress.
  • To investigate the Vattem-Wek hypothesis involving a "race to reload" mechanism.
  • To develop and analyze probabilistic models of ATF4 translation control.

Main Methods:

  • Developed two analytic, probabilistic models for ATF4 translation regulation.
  • Incorporated the Vattem-Wek hypothesis and the "race to reload" concept.
  • Considered models with uniform and non-uniform nucleotide triplet kinetic properties.
  • Analyzed initiation rate dependence on ternary complex concentration.

Main Results:

  • The models provide insights into how ATF4 translation is selectively enhanced under stress.
  • The "race to reload" mechanism involving upstream open reading frames (uORFs) is central to ATF4 regulation.
  • Model variations explore the impact of kinetic properties and initiation functions.

Conclusions:

  • The developed models offer a framework for understanding ATF4 translation control during cellular stress.
  • The findings highlight the intricate regulation of gene expression under adverse conditions.
  • Further modifications of the models can explore diverse parameters and initiation scenarios.