Monday, November 9, 2009
P29

Adjustment of Lactococcus lactis metabolism in response to specific growth rate change studied by continuous cultivation (A-stat) and metabolic flux analysis

Petri-Jaan Lahtvee, Kaarel Adamberg, Liisa Arike, Ranno Nahku, Kristo Abner, Kaspar Valgepea, and Raivo Vilu. Competence Center of Food and Fermentation Technology, Akadeemia tee 15B, Tallinn, Estonia

A comprehensive study to describe adaptive responses of Lactococcus lactis metabolism to the change of growth rate was characterized by the level of product formation (extracellular metabolome), glucose and 20 amino acid consumption, whole genome based transcriptome analysis and proteome measurements. Culture was cultivated in strictly controlled conditions on glucose limited defined medium using the accelerostat (A-stat) method in the specific growth rate range 0.1 – 0.6 h-1. This cultivation method enabled to acquire steady state data at defined conditions about production and consumption yields of measurable products and substrates to calculate intracellular fluxes using whole genome based metabolic flux analysis, containing 375 metabolites and 580 reactions.

Lactococcus lactis showed decreased formation of side products and change into homolactic fermentation by down–regulation of acetate and formate synthesis with increase of specific growth rate.  Reduced energy demands at higher growth rates was indicated by lower consumption of alternative substrates, including arginine. Metabolic shifts in response to specific growth rate were determined by measurements of 1940 gene expression with DNA microarrays and protein concentration changes using iTRAQ. Specific mechanisms for amino acid consumption and energy metabolism were postulated. Reproducibility of A-stat cultivation method was characterized by standard deviation less than 10% on the basis of omics data and metabolic flux analysis. It can be concluded that A-stat approach enables to get massive amount of steady state data faster compared to chemostat at defined environmental conditions, making it a suitable method for studying metabolic switch points in microorganisms’ growth space.

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