Mutagenesis Associated with Repair of DNA Double-Strand Breaks Under Stress

  • Chandan Shee
  • P. J. Hastings
  • Susan M. Rosenberg


Evolutionary theory predicted that mutations occur randomly both in time and in genomic space. This expectation has been revised by the discoveries of stress-induced mutation mechanisms, which activate mutagenesis pathways under the control of stress responses. Stress-induced mutation mechanisms produce mutations preferentially when cells or organisms are maladapted to their environment, i.e., when they are stressed, potentially accelerating evolution. We review stress-­induced mutagenesis associated with repair of double-strand breaks in Escherichia coli. In this mechanism, the process of DNA break repair by homologous recombination is high-fidelity in unstressed cells, but is switched to a mutagenic mode using the error-prone DNA polymerase DinB, and other error-prone DNA polymerases, under the control of the RpoS general stress response. The switch to mutagenic repair occurs during starvation or if RpoS is upregulated artificially in unstressed cells, and presumably during the many different stresses that activate the RpoS response. Recent work shows that this mechanism accounts for most spontaneous base-substitution and frameshift mutagenesis during starvation in E. coli, acts not only in plasmid DNA but also in the chromosomes of plasmid-free cells, illustrates the generality of this mechanism in many organisms and circumstances, and resolves some other old tensions in the field. Stress-induced mutation mechanisms studied in the laboratory are likely to provide superior models for mutagenesis underlying pathogen-host adaptation, antibiotic resistance, and cancer progression and resistance mechanisms, all problems of evolution under stress driven by mutations.


Mutation Mechanism Unstressed Cell Revertant Coloni Mutagenic Repair Spontaneous Frameshift 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Supported by National Institutes of Health grant R01-GM53158.


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© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Chandan Shee
    • 1
  • P. J. Hastings
    • 2
  • Susan M. Rosenberg
    • 1
  1. 1.Departments of Molecular and Human Genetics, Biochemistry and Molecular Biology, Molecular Virology and MicrobiologyDan L Duncan Cancer Center, Baylor College of MedicineHoustonUSA
  2. 2.Department of Molecular and Human GeneticsBaylor College of MedicineHoustonUSA

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