• Title of article

    Response Acceleration in Post-translationally Regulated Genetic Circuits

  • Author/Authors

    Alexander Y. Mitrophanov، نويسنده , , Eduardo A. Groisman، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2010
  • Pages
    12
  • From page
    1398
  • To page
    1409
  • Abstract
    Transcription factors must often be chemically modified to perform their functions. Yet, it is not known whether the mechanisms that bring about such modifications impact the quantitative or kinetic properties of gene expression. Phosphorylation controls the activity of regulatory proteins of the two-component system family, which constitutes a prevalent form of bacterial signal transduction. These proteins are phosphorylated/dephosphorylated by cognate sensor proteins in response to specific signals. The phosphorylation level of the regulatory proteins is also modulated by small proteins—termed connectors—that are produced when a cell experiences signals other than those detected directly by the sensors. Here, we explore how differences in the targets (i.e., sensor or regulator) and the mechanisms used by connectors to generate phosphorylated regulatory proteins affect the output of two-component systems. Our mathematical modeling demonstrates that sensor-targeting mechanisms exhibit stronger response acceleration than those where the connector targets the regulator. These differences are robust to perturbations in kinetic parameters but dependent upon the specific sensor-to-regulator ratio and how the ratio is controlled in living cells. In contrast, the steady-state output levels of the circuits are determined primarily by the circuit parameters, and can be adjusted without affecting response acceleration. Likewise, the analyzed connector-mediated circuits exhibit similar noise generation properties. Our results highlight the relationship between the architecture of genetic regulatory circuits and their dynamic properties.
  • Keywords
    Dynamics , phosphorylation , Signal transduction , two-component systems , Mathematical Modeling
  • Journal title
    Journal of Molecular Biology
  • Serial Year
    2010
  • Journal title
    Journal of Molecular Biology
  • Record number

    1251317