# Modelling of Escherichia coli Batch and Fed-Batch Processes in Semi-Defined Yeast Extract Media

## TL;DR

Researchers improved a model for Escherichia coli growth in yeast extract media, enabling better prediction and optimization of bioprocesses.

## Contribution

A novel extension to a macro-kinetic model was developed to describe E. coli growth in yeast extract-based media.

## Key findings

- The extended model accurately represents E. coli growth dynamics in fed-batch processes with yeast extract.
- The model reliably predicts growth across various yeast extract concentrations up to 20 g L−1.
- A simplified version of the model suffices for batch processes with less complex data.

## Abstract

Model-based approaches provide increasingly advanced opportunities for optimizing and accelerating bioprocess development. However, to accurately capture the complexity of biotechnological processes, continuous refinement of suitable models remains essential. A crucial gap in this field has been the lack of suitable model for describing Escherichia coli growth in cultivation media containing yeast extract, while accounting for key bioprocess parameters such as biomass, substrate, acetate, and oxygen. To address this, a published mechanistic macro-kinetic model for E. coli was extended with a set of mathematical equations that describe key aspects of the uptake of yeast extract. The underlying macro-kinetic approach is based on the utilization of amino acids in E. coli, where growth is primarily influenced by two distinct classes of amino acids. Using fed-batch cultivation data from an E. coli K-12 strain supplemented with yeast extract, it was demonstrated that the proposed model extensions were essential for accurately representing the bioprocess. This approach was further validated through fitting the model on cultivation data from five different yeast extracts sourced from various manufacturers. Additionally, the model enabled reliable predictions of growth dynamics across a range of yeast extract concentrations up to 20 g L−1. Further differentiation of the data into batch and fed-batch revealed that for less complex datasets, such as those obtained from a batch phase, a simplified model can be sufficient. Due to its modular structure, the developed model provides the necessary flexibility to serve as a tool for the development, optimization, and control of E. coli cultivations with and without yeast extract.