Search

Reprogramming of somatic cells to induced pluripotent stem cells, by overexpressing certain factors referred to as the reprogramming factors, can revolutionize regenerative medicine. To provide a coherent description of induced pluripotency from the gene regulation perspective, we use 35 microarray datasets to construct a reprogramming gene regulatory network. Comprising 276 nodes and 4471 links, the resulting network is, to the best of our knowledge, the largest gene regulatory network constructed for human fibroblast reprogramming and it is the only one built using a large number of experimental datasets. To build the network, a model that relates the expression profiles of the initial (fibroblast) and final (induced pluripotent stem cell) states is proposed and the model parameters (link strengths) are fitted using the experimental data. Twenty nine additional experimental datasets are collectively used to test the model/network, and good agreement between experimental and predicted gene expression profiles is found. We show that the model in conjunction with the constructed network can make useful predictions. For example, we demonstrate that our approach can incorporate the effect of reprogramming factor stoichiometry and that its predictions are consistent with the experimentally observed trends in reprogramming efficiency when the stoichiometric ratios vary. Using our model/network, we also suggest new (not used in training of the model) candidate sets of reprogramming factors, many of which have already been experimentally verified. These results suggest our model/network can potentially be used in devising new recipes for induced pluripotency with higher efficiencies. Additionally, we classify the links of the network into three classes of different importance, prioritizing them for experimental verification. We show that many of the links in the top ranked class are experimentally known to be important in reprogramming. Finally, comparing with other methods, we show that using our model is advantageous. [ABSTRACT FROM AUTHOR]

Cancer is one of the most troublesome diseases and a leading cause of death worldwide. Recently, novel treatments have been continuously developed to improve the disadvantages of conventional therapies, such as prodigious expenses, unwanted side effects, and tumor recurrence. Here, we provide the first non-invasive treatment that has combined epigallocatechin gallate (EGCG), the most abundant catechin in green tea, with a low strength pulsed electric field (PEF) and a low energy ultrasound (US). It has been observed that the cell viability of human pancreatic cancer PANC-1 was decreased approximately to 20% of the control after this combination treatment for 72 h. Besides, the combined triple treatment significantly reduced the high tolerance of HepG2 cells to the EGCG-induced cytotoxicity and similarly exhibited compelling proliferation-inhibitory effects. We also found the combined triple treatment increased the intracellular reactive oxygen species (ROS) and acidic vesicles, and the EGCG-induced inhibition of Akt phosphorylation was dramatically intensified. In this study, the apoptosis inhibitor Z-VAD-FMK and the autophagy inhibitor 3-MA were, respectively, shown to attenuate the anticancer effects of the triple treatment. This indicates that the triple treatment-induced autophagy was switched from cytoprotective to cytotoxic, and hence, cooperatively caused cell death with the apoptosis. Since the EGCG is easily accessible from the green tea and mild for a long-term treatment, and the non-invasive physical stimulations could be modified to focus on a specific location, this combined triple treatment may serve as a promising strategy for anticancer therapy. [ABSTRACT FROM AUTHOR]

Mitochondria play a critical role in the generation of metabolic energy and are crucial for eukaryotic cell survival and proliferation. In most sexual eukaryotes, mitochondrial DNA (mtDNA) is inherited from only one parent in non-Mendelian inheritance in contrast to the inheritance of nuclear DNA. The model organism Saccharomyces cerevisiae is commonly used to study mitochondrial biology. It has two mating types: MATa and MATα. Previous studies have suggested that the mtDNA inheritance patterns in hybrid diploid cells depend on the genetic background of parental strains. However, the underlying mechanisms remain unclear. To elucidate the mechanisms, we examined the effects of environmental factors on the mtDNA inheritance patterns in hybrids obtained by crossing S. cerevisiae with its close relative S. paradoxus. The results demonstrated that environmental factors can influence mtDNA transmission in hybrid diploids, and that the inheritance patterns are strain dependent. The fitness competition assay results showed that the fitness differences can explain the mtDNA inheritance patterns under specific conditions. However, in this study, we found that fitness differences cannot fully be explained by mitochondrial activity in hybrids under stress conditions. [ABSTRACT FROM AUTHOR]