Feedback Loops of Adipogenesis Targeted (FAT) a multi-omics approach to decipher PPARG regulators

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The obesity pandemic has become one of the most important global health issues. Worldwide, 1.4 billion people are affected causing an annual health burden of 2 trillion Euros. To uncover the origin of increased or decreased fat cell production and to find novel treatment strategies, a comprehensive understanding of the underlying regulatory mechanism is indispensable. However, so far study of fat cell differentiation has focused on single molecular layers and neglected network connectivity.FAT will apply a multi-layer network analysis combining different ‘omics’ techniques in concert with live-cell perturbation experiments for a system-wide study of network connectivity and will reveal alternative treatment strategies fat cell differentiation related dysfunction. The central question is: How is peroxisome proliferator-activated receptor gamma (PPARG), the lipid controlled master regulator of adipogenesis fine-tuned by feedback circuits and can these circuits be utilized to control the number of fat cells already at the onset of obesity? To address this, FAT will combine i) time-resolved elucidation of feedback circuits by proteomics; ii) screening and identification of lipids regulating PPARG activity using lipidomics; iii) computational network modeling to confirm known and predict new signaling nodes and iv) validate discovered regulators with in human cellular systems. Importantly, FAT will surpass classical approaches by providing a multiscale understanding of network connectivity. Monitoring absolute molecular quantities during differentiation, diet and perturbation will elucidate their connectivity and interdependence, reveal the signaling circuits and generate testable hypotheses on the function of the monitored proteins or lipids to control the number of fat cells.Thus, FAT will deliver novel insights into the molecular processes underlying obesity and open new avenues for treatment and the prevention of obesity.