Vibrio natriegens as novel workhorse for industrial biotechnology

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The productivity of industrial fermentation processes is essentially limited by the biomass-specific substrate consumption rate (qS) of the microbial system. Since the qS is dependent on the growth rate (gamma), we identified Vibrio natriegens as a potential novel workinghorse for future biotechnological processes. V. natriegens is the non-pathogenic bacterium with the highest growth rates on our planet. Preliminary work with this organism confirmed the rapid growth on BHIN complex medium with doubling times of 9.4 minutes and showed that V. natriegens can metabolize a variety of industrially relevant substrates. In addition, V. natriegens is growing both aerobically and anaerobically and shows in minimal medium with glucose exceptional high qS values of 3.90 ± 0.08 g g-1 h-1 (aerobic) and 7.81 ± 0.71 g g-1 h-1 (anaerobic), which are significantly higher than those of established microbial systems. In addition, resting cells under anaerobic conditions remained metabolically active (qS = 1.02 ± 0.05 g g-1 h-1), and the fermentation products acetate, lactate, succinate, formate, alanine and ethanol were formed with volumetric productivities (QP) ranging between 1.7 and 4.3 g L-1 h-1. The cumulative QP of the secreted products was 17.7 ± 0.1 g L-1 h-1.The overall aim of this project is to establish V. natriegens as a novel production platform for Industrial Biotechnology and to emphasize the potential of this organism for future work. In order to achieve this goal, a transcriptional and metabolic map under relevant process conditions is to be created as a basis for further Metabolic Engineering studies applying transcriptome and metabolome analyzes. The already available molecular biology toolbox will be applied to construct V. natriegens strains for the aerobic and anaerobic production of L-valine and succinate for the first time. For the developed strains, fermentation processes are to be established and optimized which are superior in their performance data to existing literature-described processes.