(451ai) A Metabolic Modeling Approach to Optimizing Recombinant Protein Production in L. Lactis Fermentations

Lactococcus lactis, a species of Lactic Acid Bacteria (LAB), continues to show great promise for use as a vaccine delivery vehicle thanks to its widespread use in the dairy industry, GRAS status, genome sequence availability, resistance to degradation in the GI tract, and susceptibility to food grade tools for genetic modification. Even so, there remain challenges in bringing this biomedical application to fruition, specifically with respect to currently attainable levels of recombinant protein expression in cultures of LAB. Recent work has optimized bioreactor conditions for recombinant protein expression in L. lactis IL1403. Under optimal bioreactor conditions, levels of Green Fluorescent Protein (GFP), a model recombinant protein, can be increased 50% per cell and 8-fold in bulk concentration over levels obtained under standard laboratory conditions. The current research aims to further increase expression through the use of genetic modification of the bacterial strain. Response surface methods, while proving to be very useful in optimizing bioreactor conditions, cannot be used to optimize genetic configuration of the host strain because genetic modifications cannot be dialed in so easily as, for example, a new temperature set point. Therefore, metabolic modeling is required to study the potential impact of plausible genetic modifications. Metabolic flux analysis (MFA) of a genome-scale L. lactis metabolic network leverages the vast available information on reaction stoichiometry to estimate the rates of all intracellular reactions, among them the reaction producing the recombinant protein. The desirability of a particular genetic modification can be estimated by using MFA to analyze the metabolic model that results from that modification. This procedure provides a basis to target particular genes for modification in progressing toward the goal of maximal recombinant protein expression.