SummaryInnate immune memory is the phenomenon whereby innate immune cells such as monocytes or macrophages undergo functional reprogramming after exposure to microbial components such as lipopolysaccharide (LPS). We apply an integrated epigenomic approach to characterize the molecular events involved in LPS-induced tolerance in a time-dependent manner. Mechanistically, LPS-treated monocytes fail to accumulate active histone marks at promoter and enhancers of genes in the lipid metabolism and phagocytic pathways. Transcriptional inactivity in response to a second LPS exposure in tolerized macrophages is accompanied by failure to deposit active histone marks at promoters of tolerized genes. In contrast, β-glucan partially reverses the LPS-induced tolerance in vitro. Importantly, ex vivo β-glucan treatment of monocytes from volunteers with experimental endotoxemia re-instates their capacity for cytokine production. Tolerance is reversed at the level of distal element histone modification and transcriptional reactivation of otherwise unresponsive genes.

Constraint-based models of metabolic networks are typically underdetermined, because they contain more reactions than metabolites. Therefore the solutions to this system do not consist of unique flux rates for each reaction, but rather a space of possible flux rates. By uniformly sampling this space, an estimated probability distribution for each reaction’s flux in the network can be obtained. However, sampling a high dimensional network is time-consuming. Furthermore, the constraints imposed on the network give rise to an irregularly shaped solution space. Therefore more tailored, efficient sampling methods are needed. We propose an efficient sampling algorithm (called optGpSampler), which implements the Artificial Centering Hit-and-Run algorithm in a different manner than the sampling algorithm implemented in the COBRA Toolbox for metabolic network analysis, here called gpSampler. Results of extensive experiments on different genome-scale metabolic networks show that optGpSampler is up to 40 times faster than gpSampler. Application of existing convergence diagnostics on small network reconstructions indicate that optGpSampler converges roughly ten times faster than gpSampler towards similar sampling distributions. For networks of higher dimension (i.e. containing more than 500 reactions), we observed significantly better convergence of optGpSampler and a large deviation between the samples generated by the two algorithms. Availability: optGpSampler for Matlab and Python is available for non-commercial use at: http://cs.ru.nl/~wmegchel/optGpSampler/.

Background Enhancers are distal regulators of gene expression that shape cell identity and control cell fate transitions. In mouse embryonic stem cells (mESCs), the pluripotency network is maintained by the function of a complex network of enhancers, that are drastically altered upon differentiation. Genome-wide chromatin accessibility and histone modification assays are commonly used as a proxy for identifying putative enhancers and for describing their activity levels and dynamics. Results Here, we applied STARR-seq, a genome-wide plasmid-based assay, as a read-out for the enhancer landscape in “ground-state” (2i+LIF; 2iL) and “metastable” (serum+LIF; SL) mESCs. This analysis reveals that active STARR-seq loci show modest overlap with enhancer locations derived from peak calling of ChIP-seq libraries for common enhancer marks. We unveil ZIC3-bound loci with significant STARR-seq activity in SL-ESCs. Knock-out of Zic3 removes STARR-seq activity only in SL-ESCs and increases their propensity to differentiate towards the endodermal fate. STARR-seq also reveals enhancers that are not accessible, masked by a repressive chromatin signature. We describe a class of dormant, p53 bound enhancers that gain H3K27ac under specific conditions, such as after treatment with Nocodazol, or transiently during reprogramming from fibroblasts to pluripotency. Conclusions In conclusion, loci identified as active by STARR-seq often overlap with those identified by chromatin accessibility and active epigenetic marking, yet a significant fraction is epigenetically repressed or display condition-specific enhancer activity.