Quantitative Modelling of Cell Metabolism

The Quantitative Modelling of Cell Metabolism team analyses quantitative multi-omics datasets, using them to produce fine-grained numerical descriptions of biological processes that can guide environmentally crucial metabolic engineering projects. We develop, publish and maintain high quality open-source software implementing our methodologies, thereby helping to promote biosustainability both inside the centre and in the broader scientific community.

What we try to achieve
We produce statistical analyses that connect measurements of intracellular metabolites, proteins and fluxes with detailed quantitative descriptions of fast regulatory mechanisms that underpin metabolism. In particular, we are interested in understanding the regulation of glycolysis and the chemical basis for overflow metabolism.

Why our research is important and how it can be used
Cell factories are a vital technology for ensuring that Earth remains habitable, but engineering cell factories is complicated, in large part due to the ubiquity of regulatory mechanisms that tend to sacrifice productivity for the sake of robustness.

Our analyses open new possibilities for the genetic engineering of cell factories, helping to pinpoint the causes of flux bottlenecks and to identify targets for gene knockouts.

How we achieve our aims – methods, tools, technologies
It has been known for over 100 years that many regulatory mechanisms can be described mathematically using systems of non-linear rate equations called kinetic models, but appropriate parameter inference has only recently become feasible due to advances in computational statistics. Great progress has also recently occurred in experimental methods for metabolite, protein and flux quantification, and it is now possible to perform statistical analyses of accurate models of key pathways using real experimental data.

Our team includes theoreticians, experimentalists, software developers and statisticians, all working together to ensure that our analyses are accurate, reproducible and actionable.

The group is headed by PI Lars Keld Nielsen and CO-PI Teddy Groves and is located at Lyngby Campus, building 220, fifth floor, room 522.