Research • Educate • Connect
Towards a sustainable bioeconomy

Research • Educate • Connect
Towards a sustainable bioeconomy
SEED FUND Project HiQFlux

Quantifying metabolic network operation in compartmentalized organisms - yeast as a eucaryotic model


The physiology of the host organisms dictates the performance of bioprocesses. Consequently, a quantitative understanding of the physiology, especially the knowledge of intracellular enzymatic reaction rates (fluxes) is key for the identification of metabolic bottlenecks and design of host and process optimization strategies.

Observing the distribution of stable 13C isotopes in intracellular metabolites and metabolic (by-)products upon addition of a 13C labelled tracer and computational interpretation of the data is the key for metabolic flux determination. 13C isotope patterns are measured by mass spectrometry (MS) yielding mass isotopomer (isotope isomer) abundance data but limited information on the positional 13C enrichment. The latter data is, however, very valuable as it increases flux identifiability and accuracy of flux estimates. Tandem-MS (MS/MS) measurements have the potential to yield positional isotopomer distributions but have so far not extensively been used in 13C-based metabolic flux analysis (13C-MFA). In HiQFlux we (i) develop a framework for the design of Tandem-MS based 13C-MFA, (ii) establish gas chromatography (GC) MS/MS measurements for the analysis of positional isotopomers of proteinogenic amino acids, and (iii) integrate the data into the 13C MFA software 13CFLUX2.

The benefit of using Tandem-MS data will be shown with the compartmentalized fluxes of acetyl-CoA and pyruvate, two key precursor metabolites for industrial relevant products, in the yeast Saccharomyces cerevisiae, an important cell factory in the bioeconomy and model system of eukaryotic organisms.

Impact on Bioeconomy

Efficient production of bio-based chemicals will be a key pillar to establish a functional bio-based economy. This implies that simple and readily available agricultural products, such as sugars, need to be converted into a range of platform chemicals in a targeted and efficient manner. However, the time required to engineer highly productive strains is extensive as even in simple unicellular microbes the interplay of all molecules resulting in a certain phenotype is not well understood. Quantitative physiology provides an in-depth insight into the metabolism and contributes to a rational engineering of whole-cell biocatalysts. HiQFlux will hence be important to overcome one of the main limitations in engineering of hyperactive biocatalysts, which efficiently convert renewable resources to valuable products. Importantly, HiQFlux will establish a generic workflow for high-quality flux analysis of microbial biocatalysts and, perspectively, of plant and mammalian cells. This opens new avenues to improve a wide range of biocatalytic processes by lifting major cellular flux constraints, increasing efficiency, specificity and economy.

Expected results/ project products

The aim of HiQFlux is to increase the determinacy and precision of metabolic fluxes in biological systems and to contribute to rational strain engineering and faster development of optimized cell factories with this metabolic insight. The computational framework is exemplarily shown for S. cerevisiae but applicable to other microorganisms and yeast like organisms, e.g., the fungus Ustilago, and extendable for the analysis of plants and mammalian cells. Hence, with HiQFlux a quantitative omics technology is added to the portfolio of the BioSC, which can be of high value for future BioSC collaborations.

Participating Core Groups

Dr. Birgitta E. Ebert / Prof. Lars M. Blank, ABBT - Angewandte Mikrobiologie, RWTH Aachen
Dr. Katharina Nöh / Prof. Wolfgang Wiechert, IBG-1 - Systembiotechnologie, Forschungszentrum Jülich

Contact (Coordinator)
Dr.-Ing. Brigitta E. Ebert
ABBT - Angewandte Mikrobiologie
RWTH Aachen
52074 Aachen
Phone: +49 241 80-26648
Fax: +49 241 80-622180

Project duration



HiQFlux is part of the NRW-Strategieprojekt BioSC and thus funded by the Ministry of Innovation, Science and Research of the German State of North Rhine-Westphalia.