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A Fermentation State Marker Rule Design Task in Metabolic Engineering.

Egils StalidzansReinis MuiznieksKonstantins DubencovsElina SileKristaps BerzinsArturs SuleikoJuris Vanags
Published in: Bioengineering (Basel, Switzerland) (2023)
There are several ways in which mathematical modeling is used in fermentation control, but mechanistic mathematical genome-scale models of metabolism within the cell have not been applied or implemented so far. As part of the metabolic engineering task setting, we propose that metabolite fluxes and/or biomass growth rate be used to search for a fermentation steady state marker rule. During fermentation, the bioreactor control system can automatically detect the desired steady state using a logical marker rule. The marker rule identification can be also integrated with the production growth coupling approach, as presented in this study. A design of strain with marker rule is demonstrated on genome scale metabolic model iML1515 of Escherichia coli MG1655 proposing two gene deletions enabling a measurable marker rule for succinate production using glucose as a substrate. The marker rule example at glucose consumption 10.0 is: IF (specific growth rate μ is above 0.060 h -1 , AND CO 2 production under 1.0, AND ethanol production above 5.5), THEN succinate production is within the range 8.2-10, where all metabolic fluxes units are mmol ∗ gDW -1 ∗ h -1 . An objective function for application in metabolic engineering, including productivity features and rule detecting sensor set characterizing parameters, is proposed. Two-phase approach to implementing marker rules in the cultivation control system is presented to avoid the need for a modeler during production.
Keyphrases
  • escherichia coli
  • wastewater treatment
  • metabolic syndrome
  • single cell
  • lactic acid
  • blood glucose
  • transcription factor
  • skeletal muscle
  • climate change
  • pseudomonas aeruginosa
  • staphylococcus aureus
  • anaerobic digestion