Using highly efficient nonlinear experimental design methods for optimization of Lactococcus lactis fermentation in chemically defined media

Abstract

Optimization of fermentation media and processes is a difficult task due to the potential for high dimensionality and nonlinearity. Here we develop and evaluate variations on two novel and highly efficient methods for experimental fermentation optimization. The first approach is based on using a truncated genetic algorithm with a developing neural network model to choose the best experiments to run. The second approach uses information theory, along with Bayesian regularized neural network models, for experiment selection. To evaluate these methods experimentally, we used them to develop a new chemically defined medium for Lactococcus lactis IL1403, along with an optimal temperature and initial pH, to achieve maximum cell growth. The media consisted of 19 defined components or groups of components. The optimization results show that the maximum cell growth from the optimal process of each novel method is generally comparable to or higher than that achieved using a traditional statistical experimental design method, but these optima are reached in about half of the experiments (73-94 vs. 161, depending on the variants of methods). The optimal chemically defined media developed in this work are rich media that can support high cell density growth 3.5-4 times higher than the best reported synthetic medium and 72% higher than a commonly used complex medium (M17) at optimization scale. The best chemically defined medium found using the method was evaluated and compared with other defined or complex media at flask- and fermentor-scales.

Multi-omics approach to study the growth efficiency and amino acid metabolism in Lactococcus lactis at various specific growth rates

“…However, there exists a remarkable lack of knowledge about the peculiarities of L. lactis metabolic regulation, especially regarding amino acid metabolism. There are several defined media designed for L. lactis [7-9], however, these are unbalanced and concentrations of individual amino acids are quite high, making their consumption measurements inaccurate as utilization by the cells is small compared to the total content. Lack of reliable information on consumption patterns and regulation of amino acid metabolism hinders design of cheaper balanced complex media and optimization of bioprocesses.…”

Switching industrial production processes from complex to defined media: method development and case study using the example of Penicillium chrysogenum

“…Up to date, proposed methods for switching microbial production processes to defined media include statistical experimental designs aiming at media optimization [7,8] as well as detailed analysis of complex media components and substitution of the relevant key components in a chemically defined form [9]. Another interesting approach suggests chemical defined media formulation based on flux analysis through the metabolic network reconstructed from the organisms genome sequence [10].…”

Impact of High-Level Expression of Heterologous Protein on Lactococcus lactis Host

“…However, expression to date has typically been orders of magnitude lower than current commercial processes utilizing Escherichia coli, Saccharomyces, Pichia, or mammalian cell systems, which commonly reach or exceed 0.5 to 2 g target protein/L. To increase the recombinant protein production, research has focused on optimization of the fermentation process, including induction strategies, environmental conditions (e.g., pH and temperature), media, and expression vector changes [6][7][8][9][10][11][12][13][14][15][16]. Despite these efforts, few studies have examined the host response to protein overproduction.…”