A robust hybrid observer for monitoring high-cell density cultures exhibiting overflow metabolism

Abstract

This work proposes a hybrid observer based on an asymptotic observer combined with an extended Kalman filter applied to high-density cultures of S. cerevisiae. The observer estimates the concentrations of biomass and ethanol, and the specific growth rate based on measurements of dissolved oxygen, carbon dioxide, and substrate (glucose). Computational simulations showed that the proposed hybrid observer could accurately detect the switch between oxidative and respiro-fermentative regimes under aerobic conditions. This switch is the metabolic signature of overflow metabolism – or Crabtree effect – in yeast. The simulations were performed under the assumption that there is no oxygen limitation, although it is controlled. Monte Carlo simulations enabled evaluation of the observer’s performance, showing stability under different metabolic regimes and a robust estimation under high measurement noise and parametric uncertainty. Furthermore, the performance of the hybrid observer was superior to classic observers like the asymptotic observer and extended Kalman filter in the simulated conditions. The proposed observer can be readily extended and applied to different cell cultures exhibiting overflow metabolism by modifying the particular process and culture parameters.