Molecular Insights into Reprogramming-Initiation Events Mediated by the OSKM Gene Regulatory Network

Somatic cells can be reprogrammed to induced pluripotent stem cells by over-expression of OCT4, SOX2, KLF4 and c-MYC (OSKM). With the aim of unveiling the early mechanisms underlying the induction of pluripotency, we have analyzed transcriptional profiles at 24, 48 and 72 hours post-transduction of OSKM into human foreskin fibroblasts. Experiments confirmed that upon viral transduction, the immediate response is innate immunity, which induces free radical generation, oxidative DNA damage, p53 activation, senescence, and apoptosis, ultimately leading to a reduction in the reprogramming efficiency. Conversely, nucleofection of OSKM plasmids does not elicit the same cellular stress, suggesting viral response as an early reprogramming roadblock. Additional initiation events include the activation of surface markers associated with pluripotency and the suppression of epithelial-to-mesenchymal transition. Furthermore, reconstruction of an OSKM interaction network highlights intermediate path nodes as candidates for improvement intervention. Overall, the results suggest three strategies to improve reprogramming efficiency employing: 1) anti-inflammatory modulation of innate immune response, 2) pre-selection of cells expressing pluripotency-associated surface antigens, 3) activation of specific interaction paths that amplify the pluripotency signal

Computational analysis of genome-wide DNA methylation during the differentiation of human embryonic stem cells along the endodermal lineage

The generation of genome-wide data derived from methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq) has become a major tool for epigenetic studies in health and disease. The computational analysis of such data, however, still falls short on accuracy, sensitivity, and speed. We propose a time-efficient statistical method that is able to cope with the inherent complexity of MeDIP-seq data with similar performance compared with existing methods. In order to demonstrate the computational approach, we have analyzed alterations in DNA methylation during the differentiation of human embryonic stem cells (hESCs) to definitive endoderm. We show improved correlation of normalized MeDIP-seq data in comparison to available whole-genome bisulfite sequencing data, and investigated the effect of differential methylation on gene expression. Furthermore, we analyzed the interplay between DNA methylation, histone modifications, and transcription factor binding and show that in contrast to de novo methylation, demethylation is mainly associated with regions of low CpG densities

Multi-omic profiles of human non-alcoholic fatty liver disease tissue highlight heterogenic phenotypes

Non-alcoholic fatty liver disease (NAFLD) is a consequence of sedentary life style and high fat diets with an estimated prevalence of about 30% in western countries. It is associated with insulin resistance, obesity, glucose intolerance and drug toxicity. Additionally, polymorphisms within, e.g., APOC3, PNPLA3, NCAN, TM6SF2 and PPP1R3B, correlate with NAFLD. Several studies have already investigated later stages of the disease. This study explores the early steatosis stage of NAFLD with the aim of identifying molecular mechanisms underlying the etiology of NAFLD. We analyzed liver biopsies and serum samples from patients with high- and low-grade steatosis (also pre-disease states) employing transcriptomics, ELISA-based serum protein analyses and metabolomics. Here, we provide a detailed description of the various related datasets produced in the course of this study. These datasets may help other researchers find new clues for the etiology of NAFLD and the mechanisms underlying its progression to more severe disease states