Kerkhoven Lab

Eduard Kerkhoven

Phone: -
E-mail: eduardk [at]
Office: Room 3054A (Fysik Origo, Kemigården 1)

Kerkhoven Lab

CV     |     Publications

Kerkhoven lab – who are we and what do we do?

Our research revolves around computational metabolic engineering, where model-driven analysis of experimental data is used to understand, predict and engineer biology. With a particular focus on metabolism we bridge the gap between in silico prediction and in vivo validation through genetic engineering. We are working on a variety of different projects, both in computational dry-lab and experimental wet-lab.

Most of our work aims to develop microbes as cell factories for sustainable production of chemicals. We work a lot with oleaginous yeasts (such as Yarrowia lipolytica and Rhodotorula toruloides) as they are able to accumulate large amount of lipids, and these lipids can either be directly used as product, or we rewire the metabolic network to produce other high-value chemicals. Other microbes we have projects on include baker’s yeast (Saccharomyces cerevisiae) and the bacteria Pseudomonas putida and Streptomyces species.

Computational analysis of metabolism helps us to come up with strategies for metabolic engineering. We reconstruct and curate genome-scale metabolic models (GEMs) for various organisms (yeasts, bacteria, human) using our RAVEN Toolbox. Our model development is tracked on GitHub, and important models are those for S. cerevisiae, Y. lipolytica, S. coelicolor and Homo sapiens. These models are combined with omics analyses (primarily RNAseq and proteomics), either directly or through the use of enzyme-constrained models using our GECKO Toolbox. In addition to biotechnological applications, we have also been using our approaches to investigate for instance evolution of the yeast subphylum, and prediction of kcat values through deep learning.

Current members of Kerkhoven lab:
Jing Fu, postdoc
Cheewin Kittikunapong, PhD student
Le Yuan, PhD student
Simone Zaghen, PhD student
Hanna Östermark, MSc student