Mid-Term Report Summary - METABOLICREGULATORS (System-wide analysis of regulatory processes that mediate at the boarder of metabolome and proteome)
The cellular metabolic network is an attractive targeted in a series of human disease, at the forefront cancer and neurodegenerative disorders. These disorders increase in the frequency with age, which is after all the consequence of cellular metabolic activity. At the same time, the metabolic network becomes vulnerable in the aged cell, and their intermediate metabolite concentrations increase in variability.
The regulatory principles controlling the underlying metabolic reactions, and that thus prevent the network to collapse when conditions change, are however only marginally understood. As the metabolic network came into being at very early stages of evolution, it presents as a sophisticated and fully optimized network, which is robust against perturbations. In MetabolicRegulators we exploit this robustness, to understand how the metabolic network operates: We systematically remove genes, and then test the influence on the stability of the metabolic network and the intermediate concentrations.
In the first half of the project, we generated genome-scale genetic resources for these studies. We noticed that very useful genetic markers, introduced in laboratory yeast strains, however compromise cellular metabolism and affect ~80% of the transcriptome and phenotypes. Therefore, we repaired these markers in around 6000 yeast strains, creating a metabolically native library containing one strain for every viable yeast gene (Muelleder et al, Nature Biotechnology, 2012). In parallel, we establish and/or develop rapid mass spectrometry techniques which are used to profile these strains systematically. The development involve targeted proteomics using selective reaction monitoring and SWATH technologies, which help to precisely quantify metabolites and proteins in whole-cell extracts (Bluemlein & Ralser, Nature protocols 2011, Vowinckel et al, F1000 Res, 2013.).
While genome-wide studies involving these methods and libraries are ongoing, we studied the regulation of central metabolism. Glycolysis and the pentose phosphate pathway are ancient chemical routes that provide the cell with energy and metabolic intermediates. In humans, dynamic regulation of these pathways plays an important role in cancer: known as the ‘Warburg effect’, many tumor cells prefer glycolysis for energy production over oxidative phosphorylation in the mitochondrial respiratory chain. We found, that one regulator of this effect, pyruvate kinase, induces a metabolic feedback loop to prevent oxidative damage. This feedback loop originates in the substrate of pyruvate kinase, and functions by inhibiting an upstream metabolic enzyme, triosephosphate isomerase (Gruening et al, Cell Metabolism, 2011). It has later been shown that this yeast-discovered mechanism is important for cancer cells (Anastasiou et al (LC Cantley lab), Science, 2011; Gruening & Ralser, Nature 2011). Meanwhile, we completed a 1.6A crystallographic structure of the enzyme bound to its inhibitor, and demonstrate its mechanism of action (Gruening et al, OpenBiology, in press).
In parallel, a novel mechanism was discovered in the genome-scale metabolism screens conducted in MetabolicRegulators. We found that cells use controlled metabolite export to time their stress response. The polyamine transporter TPO1 was found to be activated under oxidative stress and to export spermine and spermidine, two metabolites previously associated with the ageing process. This export induces a delay in cell growth, and at the same time was required for the timely induction of anti-stress proteins such as HSP70, HSP90 and HSP104 (Krueger et al, EMBO reports, 2013.). These metabolites have been associated with both the progression of cancer and with ageing, indicating that time-dependent metabolic control could be deficient in these pathological states.
The regulatory principles controlling the underlying metabolic reactions, and that thus prevent the network to collapse when conditions change, are however only marginally understood. As the metabolic network came into being at very early stages of evolution, it presents as a sophisticated and fully optimized network, which is robust against perturbations. In MetabolicRegulators we exploit this robustness, to understand how the metabolic network operates: We systematically remove genes, and then test the influence on the stability of the metabolic network and the intermediate concentrations.
In the first half of the project, we generated genome-scale genetic resources for these studies. We noticed that very useful genetic markers, introduced in laboratory yeast strains, however compromise cellular metabolism and affect ~80% of the transcriptome and phenotypes. Therefore, we repaired these markers in around 6000 yeast strains, creating a metabolically native library containing one strain for every viable yeast gene (Muelleder et al, Nature Biotechnology, 2012). In parallel, we establish and/or develop rapid mass spectrometry techniques which are used to profile these strains systematically. The development involve targeted proteomics using selective reaction monitoring and SWATH technologies, which help to precisely quantify metabolites and proteins in whole-cell extracts (Bluemlein & Ralser, Nature protocols 2011, Vowinckel et al, F1000 Res, 2013.).
While genome-wide studies involving these methods and libraries are ongoing, we studied the regulation of central metabolism. Glycolysis and the pentose phosphate pathway are ancient chemical routes that provide the cell with energy and metabolic intermediates. In humans, dynamic regulation of these pathways plays an important role in cancer: known as the ‘Warburg effect’, many tumor cells prefer glycolysis for energy production over oxidative phosphorylation in the mitochondrial respiratory chain. We found, that one regulator of this effect, pyruvate kinase, induces a metabolic feedback loop to prevent oxidative damage. This feedback loop originates in the substrate of pyruvate kinase, and functions by inhibiting an upstream metabolic enzyme, triosephosphate isomerase (Gruening et al, Cell Metabolism, 2011). It has later been shown that this yeast-discovered mechanism is important for cancer cells (Anastasiou et al (LC Cantley lab), Science, 2011; Gruening & Ralser, Nature 2011). Meanwhile, we completed a 1.6A crystallographic structure of the enzyme bound to its inhibitor, and demonstrate its mechanism of action (Gruening et al, OpenBiology, in press).
In parallel, a novel mechanism was discovered in the genome-scale metabolism screens conducted in MetabolicRegulators. We found that cells use controlled metabolite export to time their stress response. The polyamine transporter TPO1 was found to be activated under oxidative stress and to export spermine and spermidine, two metabolites previously associated with the ageing process. This export induces a delay in cell growth, and at the same time was required for the timely induction of anti-stress proteins such as HSP70, HSP90 and HSP104 (Krueger et al, EMBO reports, 2013.). These metabolites have been associated with both the progression of cancer and with ageing, indicating that time-dependent metabolic control could be deficient in these pathological states.