Dynamic CpG methylation delineates subregions within super-enhancers selectively decommissioned at the exit from naive pluripotency

Clusters of enhancers, referred as to super-enhancers (SEs), control the expression of cell identity genes. The organisation of these clusters, and how they are remodelled upon developmental transitions remain poorly understood. Here, we report the existence of two types of enhancer units within SEs typified by distinctive CpG methylation dynamics in embryonic stem cells (ESCs). We find that these units are either prone for decommissioning or remain constitutively active in epiblast stem cells (EpiSCs), as further established in the peri-implantation epiblast in vivo. Mechanistically, we show a pivotal role for ESRRB in regulating the activity of ESC-specific enhancer units and propose that the developmentally regulated silencing of ESRRB triggers the selective inactivation of these units within SEs. Our study provides insights into the molecular events that follow the loss of ESRRB binding, and offers a mechanism by which the naive pluripotency transcriptional programme can be partially reset upon embryo implantation

Dynamic CpG methylation delineates subregions within super-enhancers selectively decommissioned at the exit from naïve pluripotency

Clusters of enhancers, referred as to super-enhancers (SEs), control the expression of cell identity genes. The organisation of these clusters, and how they are remodelled upon developmental transitions remain poorly understood. Here, we report the existence of two types of enhancer units within SEs typified by distinctive CpG methylation dynamics in embryonic stem cells (ESCs). We find that these units are either prone for decommissioning or remain constitutively active in epiblast stem cells (EpiSCs), as further established in the peri-implantation epiblast in vivo. Mechanistically, we show a pivotal role for ESRRB in regulating the activity of ESC-specific enhancer units and propose that the developmentally regulated silencing of ESRRB triggers the selective inactivation of these units within SEs. Our study provides insights into the molecular events that follow the loss of ESRRB binding, and offers a mechanism by which the naive pluripotency transcriptional programme can be partially reset upon embryo implantation

Dynamic CpG methylation delineates subregions within super-enhancers selectively decommissioned at the exit from naive pluripotency.

Clusters of enhancers, referred as to super-enhancers (SEs), control the expression of cell identity genes. The organisation of these clusters, and how they are remodelled upon developmental transitions remain poorly understood. Here, we report the existence of two types of enhancer units within SEs typified by distinctive CpG methylation dynamics in embryonic stem cells (ESCs). We find that these units are either prone for decommissioning or remain constitutively active in epiblast stem cells (EpiSCs), as further established in the peri-implantation epiblast in vivo. Mechanistically, we show a pivotal role for ESRRB in regulating the activity of ESC-specific enhancer units and propose that the developmentally regulated silencing of ESRRB triggers the selective inactivation of these units within SEs. Our study provides insights into the molecular events that follow the loss of ESRRB binding, and offers a mechanism by which the naive pluripotency transcriptional programme can be partially reset upon embryo implantation

WeGET: predicting new genes for molecular systems by weighted co-expression

Contains fulltext : 155740.pdf (publisher's version ) (Open Access

Estimating metabolic fluxes using a maximum network flexibility paradigm

Motivation: Genome-scale metabolic networks can be modeled in a constraint-based fashion. Reaction stoichiometry combined with flux capacity constraints determine the space of allowable reaction rates. This space is often large and a central challenge in metabolic modeling is finding the biologically most relevant flux distributions. A widely used method is flux balance analysis (FBA), which optimizes a biologically relevant objective such as growth or ATP production. Although FBA has proven to be highly useful for predicting growth and byproduct secretion, it cannot predict the intracellular fluxes under all environmental conditions. Therefore, alternative strategies have been developed to select flux distributions that are in agreement with experimental "omics" data, or by incorporating experimental flux measurements. The latter, unfortunately can only be applied to a limited set of reactions and is currently not feasible at the genome-scale. On the other hand, it has been observed that micro-organisms favor a suboptimal growth rate, possibly in exchange for a more "flexible" metabolic network. Instead of dedicating the internal network state to an optimal growth rate in one condition, a suboptimal growth rate is used, that allows for an easier switch to other nutrient sources. A small decrease in growth rate is exchanged for a relatively large gain in metabolic capability to adapt to changing environmental conditions. Results: Here, we propose Maximum Metabolic Flexibility (MMF) a computational method that utilizes this observation to find the most probable intracellular flux distributions. By mapping measured flux data from central metabolism to the genome-scale models of Escherichia coli and Saccharomyces cerevisiae we show that i) indeed, most of the measured fluxes agree with a high adaptability of the network, ii) this result can be used to further reduce the space of feasible solutions iii) this reduced space improves the quantitative predictions made by FBA and contains a significantly larger fraction of the measured fluxes compared to the flux space that was reduced by a uniform sampling approach and iv) MMF can be used to select reactions in the network that contribute most to the steady-state flux space. Constraining the selected reactions improves the quantitative predictions of FBA considerably more than adding an equal amount of flux constraints, selected using a more naïve approach. Our method can be applied to any cell type without requiring prior information

Extensive epigenomic integration of the glucocorticoid response in primary human monocytes and in vitro derived macrophages

Glucocorticoid receptor is a transcription factor that is ubiquitously expressed. Glucocorticoids are circadian steroids that regulate a wide range of bodily functions, including immunity. Here we report that synthetic glucocorticoids affect 1035 mRNAs in isolated healthy human blood monocytes but only 165 in the respective six day-old monocyte-derived macrophages. The majority of the glucocorticoid response in monocytes concerns genes that are dynamic upon monocyte to macrophage differentiation, whereby macrophage-like mRNA levels are often reached in monocytes within four hours of treatment. Concomitantly, over 5000 chromosomal H3K27ac regions undergo remodelling, of which 60% involve increased H3K27ac signal. We find that chromosomal glucocorticoid receptor binding sites correlate with positive but not with negative local epigenomic effects. To investigate further we assigned our data to topologically associating domains (TADs). This shows that about 10% of macrophage TADs harbour at least one GR binding site and that half of all the glucocorticoid-induced H3K27ac regions are confined to these TADs. Our analyses are therefore consistent with the notion that TADs naturally accommodate information from sets of distal glucocorticoid response elements

Epigenetic modulation of a hardwired 3D chromatin landscape in two naive states of pluripotency

Contains fulltext : 203684.pdf (Publisher’s version ) (Closed access

beta-Glucan Reverses the Epigenetic State of LPS-Induced Immunological Tolerance

Contains fulltext : 163356.pdf (publisher's version ) (Open Access