Biodiesel consists of fatty acid alkyl esters and is produced via transesterification of long chain fatty acids, derived from vegetable oil, with methanol. The principle by-product of this process, which makes up to 10% of the biodiesel production, is crude glycerol. Since its purification is rather unsustainable, the microbial upgrading to value-added products opens new opportunities. Lactobacillus diolivorans metabolizes glycerol to balance its electron household by reducing the intermediate 3-hydroxypropione aldehyde to 1,3-propanediol or oxidizing it to 3-hydroxypropionic acid. This species of Lactobacillus is a very effective natural producer of 1,3-propanediol, with titers up to 90 g/L, but as well shows potential for the production of 3-hydroxypropionic acid, which is considered as one of the top twelve value-added platform compounds from biomass according to the US Department of Energy.

Research questions:

The work is based on bio-process engineering as a valuable tool to manipulate the redox household of L. diolivorans to shift the product pattern.

One target is the feeding strategy, since L. diolivorans is not able to use glycerol as sole energy source. The metabolization of sugars like glucose generates excess electrons which favor the reductive pathway for glycerol utilization. Different molar ratios of glucose to glycerol as well as other carbon sources will be tested to study their impact on the product pattern.  

Oxygen input is another parameter, which potentially allows to modulate the flow of electrons. Oxygen can serve as electron sink for many lactic acid bacteria, however, it cannot not be used as energy source for respiration.

A final goal for the thesis is metabolic engineering of the cell factory to aid the process based approach to optimize 3-HP production. 


The major part of the work will be the optimization of fed-batch processes in bioreactors to optimize 3-HP production. The basic set-up for 1,3-PDO production is known. Starting at this base case the process will be varied. Thorough analyses will allow model based improvement of the process. Finally, metabolic engineering targets will be identified. The corresponding strains will be constructed and tested under the optimized process conditions.