Dynamic analysis of a microbial process: A systems engineering approach

TLDR

The study develops a general mathematical model of a chemostat system to guide a dynamic testing experimental program. The authors cultivated glucose‑limited Saccharomyces cerevisiae in a chemostat, perturbed it with changes in glucose, dilution, pH, and temperature, measured dynamic responses of biomass, glucose, cell number, RNA, and protein, and used simulation techniques to build and compare a dynamic mathematical model with experimental data and the Monod model. The resulting model proved quantitatively accurate and superior to the Monod model, and analysis showed that adjusting intracellular RNA fraction limits the acceleration of cell‑specific growth rate.

Abstract

Abstract A general mathematical model of the chemostat system is developed in order to define an experimental program of dynamic testing. A glucose‐limited culture of Saccharomyces cerevisiae was grown in a chemostat using chemically defined medium. The chemostat was perturbed from an initial steady state by changes in input glucose concentration, dilution rate, pH, and temperature. Dynamic responses of cell mass, glucose, cell number, RNA, and protein concentrations were measured. A number of simulation techniques were used in developing a dynamic mathematical model and in comparing the developed model with experimental data as well as the Monod model. The resulting model was found to be quantitatively accurate and superior to the Monod model. The developed model was interpreted in the light of cell physiology. Adjustment of intracellular RNA fraction was found to be rate limiting in acceleration of cell specific growth rate.