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Design and Synthesis of a Reconfigurable DNA Accordion Rack
Published on: August 15, 2018
Exact solution of a model DNA-inversion genetic switch with orientational control
Paolo Visco1, Rosalind J Allen, Martin R Evans
1SUPA, School of Physics, The University of Edinburgh, Mayfield Road, Edinburgh EH9 3JZ, United Kingdom.
Physical Review Letters
|October 15, 2008
Summary
This study models DNA inversion switches in bacteria, finding that controlling recombinase production based on switch state alters system behavior. This leads to non-Poissonian switching patterns and correlated flip times.
Area of Science:
- Molecular Biology
- Biophysics
- Systems Biology
Background:
- DNA inversion is a key mechanism for reversible phenotypic switching in bacteria and bacteriophages.
- Site-specific recombinase enzymes mediate DNA inversion by flipping the orientation of short DNA elements.
- The fim switch in E. coli serves as a biological inspiration for DNA inversion dynamics.
Purpose of the Study:
- To propose and analyze a simple model of a DNA-inversion switch with orientational control.
- To investigate the impact of recombinase production dependency on switch state.
- To mathematically and computationally model the stochastic behavior of DNA inversion.
Main Methods:
- Developed an exact analytical solution for the chemical master equation of the proposed model.
- Employed stochastic simulations to analyze the switch dynamics.
- Investigated the distribution of times spent in the 'on' state and correlations between flip times.
Main Results:
- The model demonstrates that orientational control causes the DNA-inversion switch to deviate from Poissonian behavior.
- The distribution of times in the 'on' state exhibits a characteristic peak.
- Successive DNA inversion (flip) times are shown to be correlated.
Conclusions:
- Orientational control is a significant factor influencing the stochastic dynamics of DNA inversion switches.
- The findings provide insights into the regulatory mechanisms underlying phenotypic switching in microorganisms.
- The developed model and analysis contribute to understanding the biophysical principles of genetic switches.
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