The Autorepressor: a Case Study of the Importance of Model Selection

Andreas Harris, Ciaran Kelly, Harrison Steel, Antonis Papachristodoulou

    Research output: Contribution to conferencePaperpeer-review

    3 Citations (Scopus)

    Abstract

    Major challenges exist in the design of gene regulatory networks. Some of these can be addressed by the in silico modelling and design of systems prior to implementation. However, reliable modelling of a given system is predicated upon a range of simplifying assumptions which may only be valid for a limited range of architectures and experimental conditions. In this paper we study the autorepressor, also referred to as the negative autoregulator, a genetic motif common both in natural and synthetic circuits. A number of approaches to modelling the autorepressor are presented, and one of these is extended to include the impact of inducer consumption, a phenomenon frequently observed in experiments. We implement this system using the tet-repressor (TetR), and compare the in vivo data with the results of simulations using parameters taken from the literature. We demonstrate that a modelling approach that considers inducer sequestration due its binding with a transcription factor may be required to qualitatively replicate experimental results. We conclude by drawing comparisons between experimental and simulated results, and discuss approaches by which modelling could be extended to better represent observed behaviours.
    Original languageEnglish
    Pages1622-1627
    Number of pages6
    DOIs
    Publication statusPublished - 23 Jan 2018
    Event56th IEEE Annual Conference on Decision and Control, CDC 2017 - Melbourne, Australia
    Duration: 12 Dec 201715 Dec 2017

    Conference

    Conference56th IEEE Annual Conference on Decision and Control, CDC 2017
    Country/TerritoryAustralia
    CityMelbourne
    Period12/12/1715/12/17

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