In cooperation with the group of dr. M. Matz Soja and R. Gebhardt we investigated the molecular causes of first step of NAFLD, the steatosis, in mouse lines. In this study, the hedgehog (Hh) is shown as a key pathway interwinding with a circadian clock. However,the RORC pathway was not exposed. However, it is known from the literature that RORC is one of the key nuclear receptors that links lipid metabolism and the circadian clock in the liver. Background & Aims The mammalian circadian clock controls various aspects of liver metabolism and integrates nutritional signals. Recently, we described Hedgehog (Hh) signaling as a novel regulator of liver lipid metabolism. Here, we investigated crosstalk between hepatic Hh signaling and circadian rhythm. Methods Diurnal rhythms of Hh signaling were investigated in liver and hepatocytes from mice with ablation of Smoothened (SAC-KO) and crossbreeds with PER2::LUC reporter mice. By using genome-wide screening, qPCR, immunostaining, ELISA and RNAi experiments in vitro we identified relevant transcriptional regulatory steps. Shotgun lipidomics and metabolic cages were used for analysis of metabolic alterations and behavior. Results Hh signaling showed diurnal oscillations in liver and hepatocytes in vitro. Correspondingly, the level of Indian Hh, oscillated in serum. Depletion of the clock gene Bmal1 in hepatocytes resulted in significant alterations in the expression of Hh genes. Conversely, SAC-KO mice showed altered expression of clock genes, confirmed by RNAi against Gli1 and Gli3. Genome-wide screening revealed that SAC-KO hepatocytes showed time-dependent alterations in various genes, particularly those associated with lipid metabolism. The clock/hedgehog module further plays a role in rhythmicity of steatosis, and in the response of the liver to a high fat diet or to differently timed starvation. Conclusions For the first time, Hh signaling in hepatocytes was found...
COBISS.SI-ID: 34207961
Nonalcoholic fatty liver disease (NAFLD) is the most frequent liver disease in the world. It describes a term for a group of hepatic diseases including steatosis, fibrosis, and cirrhosis that can finally lead to hepatocellular carcinoma. There are many factors influencing NAFLD initiation and progression, such as obesity, dyslipidemia, insulin resistance, genetic factors, and hormonal changes. However, there is also lean-NAFLD which is not associated with obesity. NAFLD is considered to be a sexually dimorphic disease. In most cases, men have a higher prevalence for the disease compared to premenopausal women. Areas covered: In this review, we first summarize the NAFLD disease epidemiology, pathology, and diagnosis. We describe NAFLD progression with the focus on sexual and genetic differences for disease development and pharmacological treatment. Personalized treatment for multifactorial NAFLD is discussed in consideration of different factors, including genetics, gender and sex. Expert opinion: The livers of female and male NAFLD patients have different metabolic capacities which influence the metabolism of all drugs applied to such patients. This aspect is not yet sufficiently taken into account. The liver computational models might quicken the pace toward assessing personalized disease progression and treatment options.
COBISS.SI-ID: 33867993
Gene regulatory networks with different topological and/or dynamical properties might exhibit similar behavior. System that is less perceptive for the perturbations of its internal and external factors should be preferred. Methods for sensitivity and robustness assessment have already been developed and can be roughly divided into local and global approaches. Benefits of both families of approaches compose so called ’glocal’ approaches were developed that apply global and local approaches in an effective and rigorous manner. We present a computational approach for ’glocal’ analysis of viable parameter regions in biological models. The methodology is based on the exploration of high-dimensional viable parameter spaces with global and local sampling, clustering and dimensionality reduction techniques. The proposed methodology allows us to efficiently investigate the viable parameter space regions, evaluate the regions which exhibit the largest robustness, and to gather new insights regarding the size and connectivity of the viable parameter regions. We evaluate the proposed methodology on three different synthetic gene regulatory network models, i.e. the repressilator model, the model of the AC-DC circuit and the model of the edge-triggered master-slave D flip-flop.
COBISS.SI-ID: 1538345411