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Cell-cycle-synchronized, oscillatory expression of a negatively autoregulated gene in E. coli

Zach Hensel,T. Marquez-Lago

Published 2015 in arXiv: Quantitative Methods

ABSTRACT

Engineering genetic networks to be both predictable and robust is a key challenge in synthetic biology. Synthetic circuits must reliably function in dynamic, stochastic and heterogeneous environments, and simple circuits can be studied to refine complex gene-regulation models. Although robust behaviours such as genetic oscillators have been designed and implemented in prokaryotic and eukaryotic organisms, a priori genetic engineering of even simple networks remains difficult, and many aspects of cell and molecular biology critical to engineering robust networks are still inadequately characterized. Particularly, periodic processes such as gene doubling and cell division are rarely considered in gene regulatory models, which may become more important as synthetic biologists utilize new tools for chromosome integration. We studied a chromosome-integrated, negative-feedback circuit based upon the bacteriophage {\lambda} transcriptional repressor Cro and observed strong, feedback-dependent oscillations in single-cell time traces. This finding was surprising due to a lack of cooperativity, long delays or fast protein degradation. We further show that oscillations are synchronized to the cell cycle by gene duplication, with phase shifts predictably correlating with estimated gene doubling times. Furthermore, we characterized the influence of negative feedback on the magnitude and dynamics of noise in gene expression. Our results show that cell-cycle effects must be accounted for in accurate, predictive models for even simple gene circuits. Cell-cycle-periodic expression of {\lambda} Cro also suggests an explanation for cell-size dependence in lysis probability and an evolutionary basis for site-specific {\lambda} integration.

PUBLICATION RECORD

  • Publication year

    2015

  • Venue

    arXiv: Quantitative Methods

  • Publication date

    2015-06-29

  • Fields of study

    Biology, Engineering

  • Identifiers
    arXiv 1506.08596
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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