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Muscle satellite stem cells (MuSCs) are responsible for skeletal muscle growth and regeneration. Despite their differentiation potential, human MuSCs have limited in vitro expansion and in vivo migration capacity, limiting their use in cell therapies for diseases affecting multiple skeletal muscles. Several protocols have been developed to derive MuSC-like progenitors from human induced pluripotent stem (iPS) cells (hiPSCs) to establish a source of myogenic cells with controllable proliferation and differentiation. However, current hiPSC myogenic derivatives also suffer from limitations of cell migration, ultimately delaying their clinical translation. Here we use a multi-disciplinary approach including bioinformatics and tissue engineering to show that DLL4 and PDGF-BB improve migration of hiPSC-derived myogenic progenitors. Transcriptomic analyses demonstrate that this property is conserved across species and multiple hiPSC lines, consistent with results from single cell motility profiling. Treated cells showed enhanced trans-endothelial migration in transwell assays. Finally, increased motility was detected in a novel humanised assay to study cell migration using 3D artificial muscles, harnessing advanced tissue modelling to move hiPSCs closer to future muscle gene and cell therapies.

Background and aimsLiver receptor homolog-1 (LRH-1; NR5A2) is a nuclear receptor that regulates metabolic homeostasis in the liver. Previous studies identified phosphatidylcholines as potential endogenous agonist ligands for LRH-1. In the liver, distinct subsets of phosphatidylcholine species are generated by two different pathways: choline addition to phosphatidic acid through the Kennedy pathway and trimethylation of phosphatidylethanolamine through phosphatidylethanolamine N-methyl transferase (PEMT).Approach and resultsHere, we report that a PEMT-LRH-1 pathway specifically couples methyl metabolism and mitochondrial activities in hepatocytes. We show that the loss of Lrh-1 reduces mitochondrial number, basal respiration, beta-oxidation, and adenosine triphosphate production in hepatocytes and decreases expression of mitochondrial biogenesis and beta-oxidation genes. In contrast, activation of LRH-1 by its phosphatidylcholine agonists exerts opposite effects. While disruption of the Kennedy pathway does not affect the LRH-1-mediated regulation of mitochondrial activities, genetic or pharmaceutical inhibition of the PEMT pathway recapitulates the effects of Lrh-1 knockdown on mitochondria. Furthermore, we show that S-adenosyl methionine, a cofactor required for PEMT, is sufficient to induce Lrh-1 transactivation and consequently mitochondrial biogenesis.ConclusionsA PEMT-LRH-1 axis regulates mitochondrial biogenesis and beta-oxidation in hepatocytes.

AimsQuantitative imaging of glutathione (GSH) with high spatial and temporal resolution is essential for studying the roles of GSH in redox biology. To study the long-standing question of compartmentalization of GSH, especially its distribution between the nucleus and cytosol, an organelle-targeted quantitative probe is needed.ResultsWe developed a reversible reaction-based ratiometric fluorescent probe-HaloRT-that can quantitatively measure GSH dynamics with subcellular resolution in real time. Using HaloRT, we quantitatively measured the GSH concentrations in the nucleus and cytosol of HeLa cells and primary hepatocytes under different treatment conditions and found no appreciable concentration gradients between these two organelles. Innovation and Conclusion: We developed the first reversible ratiometric GSH probe that can be universally targeted to any organelle of interest. Taking advantage of this new tool, we provided definitive evidence showing that GSH concentrations are not significantly different between the nucleus and cytosol, challenging the view of nuclear compartmentalization of GSH.

UnlabelledBalance of labile methyl groups (choline, methionine, betaine, and folate) is important for normal liver function. Quantitatively, a significant use of labile methyl groups is in the production of phosphatidylcholines (PCs), which are ligands for the nuclear liver receptor homolog-1 (LRH-1). We studied the role of LRH-1 in methyl-pool homeostasis and determined its metabolic effects using the methionine and choline-deficient (MCD) diet, which depletes methyl groups and results in a deleterious decrease in the PC-to-phosphatidylethanolamine ratio. We found that MCD diet-fed, liver-specific LRH-1 knockout mice (Lrh-1(-/-) ) do not show the expected decreased methyl-pool and PC/phosphatidylethanolamine ratio and are resistant to the hepatitis and fibrosis normally induced by the diet. Adaptive responses observed in wild-type mice on the MCD diet were also observed in Lrh-1(-/-) mice on a normal diet. This includes reduced expression of the highly active glycine-n-methyltransferase and the biliary phospholipid floppase multidrug-resistance protein 2 (Mdr2/Abcb4), resulting in reduced consumption of methyl groups and biliary PC secretion. In vitro studies confirm that Gnmt and Mdr2 are primary LRH-1 target genes. Additional similarities between hepatic gene expression profiles in MCD diet-fed wild-type and untreated Lrh-1(-/-) mice suggest that methyl-pool deficiency decreases LRH-1 activity, and this was confirmed by in vitro functional results in cells maintained in MCD medium.ConclusionLRH-1 is a novel transcriptional regulator of methyl-pool balance; when the methyl-pool is depleted, decreased LRH-1 transactivation suppresses expression of key genes to minimize loss of labile methyl groups. (Hepatology 2016;63:95-106).

The dissertation consists of two different topics. The first topic is to develop the methodologies in optimizing the ROC (Receiver Operating Characteristic) curve with variable selection based on group sparsity. An ROC curve is a popular tool in the classification of two populations. The nonparametric additive model is used to construct a classifier which is estimated by maximizing the U-statistic type of empirical AUC (Area Under Curve). In particular, the sparsity situation is considered in the sense that only a small number of variables is significant in the classification, so it is demanded that lots of noisy variables will be removed. Some theoretical result on the necessity of variable selection under the sparsity condition is provided since the AUC of the classifier from maximization of empirical AUC is not guaranteed to be optimal. To select significant variables in the classification, the grouped lasso which has been widely used when groups of parameters need to be either selected or discarded simultaneously is used. In addition, the performance of the proposed method is evaluated by numerical studies including simulation and real data examples compared with other existing approaches. The second topic is developing the hypothesis test for non-equivalence. We consider the problem of testing the non-equivalence of several independent normal population means. Testing homogeneity of several population means usually refers to testing the exact equality of population means. Instead of determining the exact homogeneity or equality, one may consider more flexible homogeneity which allows a predetermined level of difference. This problem is known as testing the non-homogeneity of populations. We propose the plug-in tests for three different measures of variability: the sum of the absolute deviations, the maximum of the absolute deviations, and the range for testing non-equivalence. For each test, the least favorable configuration (LFC) to ensure the maximum rejection probability under the null hypothesis is investigated. Furthermore, we demonstrate the numerical studies based on both simulations and real data to evaluate the plug-in tests and compare our proposed tests with other possible tests.