Nicolas Sundqvist

Investigating complex biological systems, such as cellular metabolism, is a long-standing field of research spanning and combining areas such as cellular physiology, biochemistry and biotechnology. While the metabolic phenotype in cellular metabolism can be characterised by many different parameters, arguably some of the most important parameters are the intracellular metabolic conversion rates, also called metabolic fluxes. These fluxes describe how metabolite conversions occur throughout a metabolic system. Describing and mapping how these fluxes interconnect, into larger metabolic networks, is one of the cornerstones of metabolic engineering.

However, metabolic fluxes are very difficult to measure in living tissue. Currently, the approach of 13C metabolic flux analysis (13C MFA) provides the best solution for quantitatively determining the metabolic fluxes. Metabolic flux analysis uses mathematical modelling to quantify the metabolic fluxes based on the metabolic distribution of isotopically labelled substrates. In the past the 13C MFA approach have mainly been used for mapping the metabolism of simpler organism such as E-coli and have only to a limited extent been used to evaluate more complex systems, such as the human cellular metabolism. While MFA can have been showed to accurately determine the flux configuration of complex systems, the modelling part of the methodology needs to be further developed. Thus, the aim of my project is to expand on the existing modelling framework in order to develop a robust, reliable and realistic methodology for modelling metabolic fluxes in human systems.

Further, I will aim to combine the knowledge acquired from my metabolic models with a mechanistic understanding for the cerebral activity and blood flow, also gained through mathematical modelling, to gain a more wholistic understanding of how the human cerebral metabolism works.