Quantitative and predictive understanding of dynamic signal transduction and gene regulation of the coding and the non-coding genome in model organisms and human disease.
A current molecular medicine topic of interest is how cells respond dynamically to changes in their environment utilizing their cellular gene, RNA and protein networks. We aim to approach this question by investigating endogenous signal transduction and transcriptional regulatory networks of coding and non-coding RNA in yeast and mammalian cells. Yeast is an ideal model organism for studying these questions because it can be easily manipulated genetically and many biological principles are conserved in humans. The regulatory principles discovered in yeast will then be tested in healthy and diseased mammalian tissue to test their generality. We aim to investigate the architecture and functioning of these networks by measuring the dynamics of protein and RNA levels in single cells. Our research methods include a combination of single-cell techniques such as flow cytometry, live cell time-lapse microscopy, fluorescent in-situ hybridization with single-molecule resolution at the RNA level (single-molecule RNA-FISH) in cells and tissue samples as well as single-molecule-based modeling. The main advantage to quantify single cells is to distinguish between different regulatory mechanisms, which cannot be observed in population-based experiments. Since our approach is general, it can lead to similar quantitative understanding of many genes, pathways or organisms ranging from yeast to human.