A model for L-methionine production describing oxygen - Productivity relationship

Amalendu Prakash Ranjan, Rajib Nayak, James Gomes

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Abstract

Background: The state-time profile of cell mass, substrate and methionine concentrations of amethionine synthesis process shows strongly nonlinear features. A mathematical representation of this process was developed that conformed to systems analysis required for monitoring and controlling methionine production. The specific growth rate was defined by an exponential term to describe the lag phase ingrowth, extended before theonset of methionine production and substrate inhibition observed for this process. A switching function was used to describe the relation between methionine synthesis and dissolved oxygen concentration. In addition, the product formation kinetics of this model described the reutilization of methionine feedback regulation whenever the residual substrate concentration dropped below a critical value. Results: The parameters for the model were determined from experimental data using a nonlinear regression technique. A complete nonlinear systems analysis of the model proved that using this model, the system was controllable and observable. The model prediction of methionine production in controlled and uncontrolled environments was satisfactory. Six statistical measures were employed to validatemodel prediction and its adequacy was shown through simulations. Conclusions: The proposed model for methionine production possesses the correct system architecture for application in process control. It predicts satisfactorily the relationship between methionine synthesis and dissolved oxygen, and time profiles of state variables.

Original languageEnglish
Pages (from-to)662-674
Number of pages13
JournalJournal of Chemical Technology and Biotechnology
Volume84
Issue number5
DOIs
Publication statusPublished - 24 Jun 2009

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Keywords

  • Controllability
  • Corynebacterium lilium
  • Metabolic switch
  • Methionine production
  • Nonlinear systemsanalysis
  • Observability
  • Parameter sensitivity
  • Statistical analysis

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