BACTERIAL GROWTH ON MULTIPLE SUBSTRATES. EXPERIMENTAL VERIFICATION OF CYBERNETIC MODELS (DIAUXIE, OPTIMIZATION)

DHINAKAR SATHYANATHAN KOMPALA, Purdue University

Abstract

Bacterial growth on multiple substrates exhibits a strikingly optimal phenomenon of consuming the fastest substrate first in a strict order of preference. The microbial regulatory processes of catabolite repression of enzyme synthesis and catabolite inhibition of enzyme activity play an important role in this optimal growth behavior on multiple substrates. A cybernetic approach of treating these complex regulatory mechanisms as the net outcome of cellular strategies of optimization is adopted here for modeling bacterial growth on multiple substrates. The models proposed here view the cellular response to a given environment as based on an instantaneous optimization strategy. The cybernetic model is developed from a modified Monod equation for growth on a single substrate, that recognizes the key function of catabolic enzymes in assimilation of the substrate. The regulatory processes of induction/repression controlling the enzyme synthesis and inhibition/activation controlling the enzyme activity are brought into the model with two sets of cybernetic variables. These variables are determined with appropriate strategies of optimization to maximize the bacterial growth rate. The model simulations are tested against experimental data obtained for the batch aerobic growth of Klebsiella oxytoca on various combinations of substrates. All the model parameters are determined from growth data on single substrates. With just these parameters, the cybernetic model is found to predict accurately the well-known 'diauxie' phenomenon and its variations due to the effects of (1) preculturing the inoculum on different substances, and (2) varying the substrate concentration. The triauxic growth phenomenon and the perturbed batch growth are also predicted by this model, without any other input as to the order in which the substrates are preferred. A simplified model for growth on two substrates, having common catabolic pathways predicts the observed sequential growth on glucose and fructose without any diauxic lag. Further, the cybernetic models have been shown to simulate the continuous culture transients as observed in experiments. It is also able to reconcile the so-called 'anomalous' behaviors in batch and continous cultures with respect to sequential and simultaneous utilizations, respectively, of the same substrate mixtures.

Degree

Ph.D.

Subject Area

Chemical engineering

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