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A systematic search for switch-like behavior in type II toxin-antitoxin systems.

Cody E FitzGerald1, James P Keener2

  • 1Department of Mathematics, University of Utah, 155 South 1400 East, Salt Lake City, UT, 84112, USA. cfitz@math.utah.edu.

Journal of Mathematical Biology
|May 16, 2021
PubMed
Summary

Gene regulatory networks exhibit bistability, crucial for cellular decisions. This study reveals how type II toxin-antitoxin systems achieve bistability, impacting persister cell dormancy.

Keywords:
BistabilityCross-talkMathematical modelingResultantResultant analysisSwitchesSynergyToxin–antitoxin systemsType II toxin–antitoxin systems

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Area of Science:

  • Molecular Biology
  • Systems Biology
  • Mathematical Biology

Background:

  • Bistable switch-like behavior is common in gene regulatory networks, enabling cellular decision-making.
  • Type II toxin-antitoxin (TA) systems are implicated in regulating persister cell dormancy via toxin concentration bistability.
  • Recent retractions necessitate a re-evaluation of TA systems' role in persister cell mechanisms and dormancy.

Purpose of the Study:

  • To investigate the mechanisms underlying bistability in type II TA systems.
  • To explore how common biological mechanisms and synergistic interactions influence toxin bistability.
  • To identify mathematical tools for delineating bistability in biological systems.

Main Methods:

  • Systematic modification of a basic RelBE type II TA system model.
  • Integration of common biological mechanisms into the model.
  • Application of Descartes' rule of signs and the resultant for bistability analysis.

Main Results:

  • A novel combination of mechanisms contributing to bistability in type II TA systems was identified.
  • Synergistic interactions between paired type II TA systems were shown to drive toxin bistability.
  • Descartes' rule of signs and the resultant proved effective in identifying bistability across mathematical systems.

Conclusions:

  • Bistability in type II TA systems can emerge from specific combinations of biological mechanisms.
  • Interactions between TA systems play a key role in establishing toxin concentration bistability.
  • Mathematical tools offer robust methods for detecting bistability in complex biological models.