I propose to decipher the unresolved molecular paradox of positive versus negative gene regulation by the Glucocorticoid Receptor (GR). GR is one of the most potent anti-inflammatory drug targets in clinical use today, and one of the most powerful metabolic regulators. Unfortunately, its unique ability to efficiently shut off inflammatory gene expression is accompanied by serious side effects. These undesired effects are attributed to the transcriptional activation of its metabolic target genes and limit its therapeutic use. SILENCE uses cutting-edge genome-wide approaches to identify the molecular mechanisms underlying the transcriptional repression, or silencing, of inflammatory genes by GR. The general, open question I want to address is how one transcription factor can simultaneously both activate and repress transcription. GR is a member of the nuclear hormone receptor family of ligand-gated transcription factors. Upon hormone binding, GR can regulate gene expression both positively and negatively, but the mechanism governing this choice is unknown. I have previously shown that classical models and existing paradigms are insufficient to explain GR-mediated gene silencing. Therefore, I postulate the existence of unknown coregulator proteins, cis-regulatory DNA sequences, noncoding RNAs, or combinations thereof. To test these hypotheses, I plan 1. a large scale RNAi screen to identify those cofactors that specify repression versus activation, 2. ChIP-exo experiments to map genomic GR binding sites at an unprecedented resolution, and 3. GRO-Seq studies to define the role of noncoding RNAs during the silencing of inflammatory genes. Inflammation is known to contribute to the pathogenesis of numerous human illnesses, including cancer, autoimmune diseases, diabetes and cardiovascular disease. Understanding the specific mechanisms involved in the silencing of inflammatory gene expression carries transformative potential for novel therapies and safer drugs.

During differentiation, dramatic changes occur in the biochemical processes and the architecture of cells. The subcellular localization of proteins greatly impacts their function and also the transformations during cell differentiation are accompanied or facilitated by protein translocation. In the proposed research project, I want to systematically study how proteins translocate during the differentiation from neuronal stem cells into neurons and astrocytes. To this end, I aim to develop a general and efficient screening method for protein translocation during cell differentiation. I envision to identify protein translocation behavior that is essential for neurodevelopment and direct reprogramming, which I plan to confirm in brain organoids, which include diverse cell types. Additionally, I want to study the underlying mechanisms both initiating and initiated by protein translocation. The method will be based on fluorescence microscopy, which will allow me to observe the dynamics of protein localization in living, differentiating cells. To increase the efficiency of the screening approach, I want to implement a recently published multiplexing strategy, temporally multiplexed imaging (TMI). This method uses the photo-switching kinetics of the utilized fluorescent protein (FP) labels to deconvolute up to 6 signals in a single spectral channel. In this way, I can label several proteins per cell multiplying the efficiency of the method and enabling the screening of a large panel of proteins. I will label these proteins with TMI-compatible FPs through gene editing. Imaging of the edited cells throughout the differentiation process and subsequent automated image analysis will identify translocating proteins. The gained mechanistic knowledge about neuronal cell differentiation will improve our basic understanding of this process eventually facilitating the development of improved disease models as well as medical applications such as reprogramming.

Pregnancy is characterized by the development of maternal insulin resistance and increased hepatic glucose production to provide sufficient glucose to be used as nutrient by the developing fetus. The maternal insulin-producing beta-cells expand to counterbalance the increased glucose levels and failure of this process can lead to development of gestational diabetes, which has great health implications for both the mother and the developing fetus. Yet, our knowledge on the mechanisms behind the pregnancy-induced beta-cell expansion in humans is limited. To address this knowledge gap, in the betaPPreg project, I will use the pig model as an ideal surrogate large mammal to study the mechanisms and identify physiological drivers of pregnancy-induced beta-cell expansion. First, I will identify the extent and the different cellular mechanisms of beta-cell adaptation in the porcine pancreas over the three trimesters of gestational time (~114 days) by histological analysis. To reveal the physiological candidates of beta-cell adaptation, I will perform untargeted metabolomics coupled with proteomics analysis of serum and pancreas at sequential temporal windows during gestation. This analysis will point to the significantly changed metabolites and growth factors that can be potentially involved in beta-cell expansion. I will perform a small-scale metabolite/growth factor screen in isolated neonatal porcine islets with the most regulated factors, to causatively link the metabolites/growth factors stimulating beta-cell expansion. The most promising candidates will be then tested in isolated human islets and human-derived ductal organoids to assess their translational potential as beta-cell proliferation/differentiation inducers and human therapeutics. Overall, the proposed project will greatly advance our understanding of beta-cell adaptation during pregnancy in large mammals and provide novel therapeutic candidates for gestational diabetes treatment.