Abstract
Our increasingly interconnected and globalized world relies heavily on a constant supply of a large variety of chemical compounds. Many of these compounds come from unsustainable sources, causing climate change and environmental destruction. Microbial cell factories have emerged as a promising alternative, and have already been shown to convert renewable substrates into a variety of useful compounds such as biofuels, plastic precursors, food supplements, and medicines. This thesis investigates the potential of the oleaginous yeast Yarrowia lipolytica to be engineered to produce fatty alcohols. Fatty alcohols are an important group of compounds widely used throughout society, for example in personal care products such as hand creams, shampoos, hair conditioners, and liquid soap. Firstly, the thesis describes EasyCloneYALI, a genetic engineering toolbox, which allows for simple and rapid engineering of Y. lipolytica using either the traditional selection marker-based integration system or a marker-free Cas9-based system. Secondly, a method book chapter based on the EasyCloneYALI method is presented. Thirdly, the thesis employs a multi-omics analysis of the cellular response to fatty alcohol production in the yeasts S. cerevisiae and Y. lipolytica. The multi-omics analysis consists of transcriptomics, metabolomics, and 13C-fluxomics. Fourthly, the thesis evaluates a data-driven engineering strain design based on key findings in the multi-omics study. In conclusion, this thesis presents an improved Y. lipolytica genetic engineering toolbox, and explores how multi-omics data and data-driven design might aid in strain development.
Info
Thesis PhD, 2020
UN SDG Classification
DK Main Research Area
Science/Technology
