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Modelling a synthetic genetic oscillator
 

Modelling a synthetic genetic oscillator

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    Modelling a synthetic genetic oscillator Modelling a synthetic genetic oscillator Presentation Transcript

    • Modeling a synthetic genetic oscillator
      Part of an iGem project
    • iGem
      Global synthetic biology competition
      International Genetically Engineered Machine
      8th year in a row, first time Wageningen UR competes
      Genetic building blocks
    • Projects
    • Synchronized Oscillatory System
      Negative feedback loops
      Positive feedback for signaling molecule
      Signaling molecule synchronizes oscillations
    • The Danino et. al scheme
    • Equations from Danino et. al
    • Advantages of this model
      4 differential equations
      Simplified reaction scheme
      Takes the surrounding physics into account
      Cell density
    • Modeling results
      Equations introduced in Matlab
      The P function is covered by dde23
    • Disadvantages of the model
      Units of parameters
      Some biologically relevant information missing
      No useful result can be extracted
    • Alternative model
      More biologically relevant and accurate
    • Equations for this model
      Y1 : lux-I mRNA
      Y2 : LUX-I protein
      Y3 : AHL
      Y4 : AHL-LUX-R complex
      Y5 : aiia mRNA
      Y6 : AiiA protein
      Y7 : AiiA-AHL complex
      Y8 : gfp mRNA
      Y9 : GFP
    • Disadvantages of this model
      Many parameters
      A large number of them unknown
      Does not (yet) take into account flow rates or cell density
    • The microsieve
    • Modeling of the microsieve
      A more global approach
      Units are more logical
      A more widely applicable model
      However:
      Many measurements are needed to validate the model
      Many physical units are required
    • Measurement plans
      Introduce different flow rates to the system
      Measure both the outflow and permeate flow (under influence of pressure)
      Introduce a cell suspension to the system
      Measure flow rates
    • Goal
      Produce a model that can estimate a flow rate to achieve:
      An appropriate cell density
      A constant oscillation through AHL expression
    • Questions
      In which way do we model this most efficiently?
      Which of these models is actually feasible?
      Is it possible to combine the models?
    • Questions?