The industrial applicability of these technologies is limited by the difficulty of achieving relevant productivities when using microorganisms fed exclusively with CO2.
These limitations are usually addressed by rewiring the metabolism of these microorganisms through genetic manipulations.
However, this approach is costly and excludes the use of a wide diversity of microorganisms presenting features of industrial interest for which genetic engineering tools have not been developed yet.
An alternative to the latter is to use mixed carbon sources in fermentations as these could also address the limitations of CO2-converting technologies, but in a much cheaper and straightforward way, and with a much wider applicability in industrial fermentation processes.
The goal of this project is to develop a tool combining computational and experimental work able to deliver an optimum productivity in fermentation processes through the selection of optimal mixed carbon sources based on model predictions. The implementation of this tool will be demonstrated in a process converting CO2 into lipids.
However, the tool developed would be applicable to a wide range of other fermentation processes, for which this work is expected to bring significant advancements and have great impact on the current fermentation technology landscape.
Supervisors:
Hariklia N. Gavala, DTU Chemical Engineering
Gregory Stephanopoulos, (Department of Chemical Engineering, Massachusetts Institute of Technology)