Most diseases, including cancer, are associated with profound metabolic changes at the cellular level. It is increasingly appreciated that tumour microenvironments contain several cell types with distinct metabolic characteristics that support cancer cells through poorly understood mechanisms. Although recent developments in analytical technologies have accelerated discoveries in the metabolic basis of cancer, there are no suitable experimental tools to study specific metabolic processes at the single-cell level. Consequently, little is know about the influence of metabolic heterogeneity within the tumour microenvironment on cancer development.
The specific project will make use of RNA biosensors in various mouse models of metabolic disease and cancer available in our lab, to study intercellular heterogeneity in the mammalian liver. Single-cell imaging of the biosensors in living mice will be performed using intravital microscopy. The student will also use complementary methods (NMR and mass spectrometry-based metabolomics, genetics, cell biology) to validate and characterise existing and newly-generated biosensors both in vivo and in cultured primary cells. In addition to covering an exciting new research area at the interface of RNA biology and metabolism, this project will provide important insights into the contribution of intercellular metabolic co-operation in liver disease.
We have recently proposed that cell can “measure” metabolic flux. In this project, we will investigate flux-sensing in yeast, using a combination of methods from systems biology, i.e. 13C flux analysis, metabolomics, mathematical modeling. Once we understand how the glycolytic flux is sensed in yeast, we will investigate whether a too low glycolytic flux will force cells entering the highly relevant quiescence state (G0). At this point, we will then also use microfluidics combined with time-lapse fluorescence microscopy and the molecular sensors developed in this network to zoom into single cells.
Kochanowski K, Volkmer B, Gerosa L, Haverkorn van Rijsewijk BR, Schmidt A, Heinemann M (2013) Functioning of a metabolic flux sensor in Escherichia coli. Proceedings of the National Academy of Sciences of the United States. 110, 1130-1135. LINK: http://www.ncbi.nlm.nih.gov/pubmed/23277571
Kotte O, Zaugg JB, Heinemann M (2010) Bacterial adaptation through distributed sensing of metabolic fluxes. Molecular Systems Biology, 6: 355. LINK: http://www.ncbi.nlm.nih.gov/pubmed/20212527
We have recently obtained evidence that yeast metabolism oscillates and that the oscillating metabolism could provide dynamic triggers for cell cycle progression. Here, by making use of RNA-based sensors for so-called flux-signaling metabolites, we would like to unravel the mechanistic basis of the connection between metabolism and cell cycle. For this work, we will use a number of different techniques, such as microscopy, microfluidics, 13C flux analysis, metabolomics, molecular biology, genetics, and many more.
Huberts DHEW, Lee SS, Gonzalez J, Janssens GE, Avalos Vizcarra I, Heinemann M (2013) Construction and use of a microfluidic dissection platform for long-term imaging of cellular processes in budding yeast. Nature Protocols. 8, 1019–1027. http://www.ncbi.nlm.nih.gov/pubmed/23640166
Lee SS, Avalos Vizcarra I, Huberts DHEW, Lee LP, Heinemann M (2012) Whole lifespan microscopic observation of budding yeast aging through a microfluidic dissection platform. Proceedings of the National Academy of Sciences of the United States, 109: 4916–4920. LINK: http://www.ncbi.nlm.nih.gov/pubmed/22421136