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Embryonic stem (ES) cells are considered to exist in a ground state if shielded from differentiation triggers. Here we show that FGF4 and TGFβ signaling pathway inhibitors, designated R2i, not only provide the ground state pluripotency in production and maintenance of naïve ES cells from blastocysts of different mouse strains, but also maintain ES cells with higher genomic integrity following long-term cultivation compared with the chemical inhibition of the FGF4 and GSK3 pathways, known as 2i. Global transcriptome analysis of the ES cells highlights augmented BMP4 signaling pathway. The crucial role of the BMP4 pathway in maintaining the R2i ground state pluripotency is demonstrated by BMP4 receptor suppression, resulting in differentiation and cell death. In conclusion, by inhibiting TGFβ and FGF signaling pathways, we introduce a novel defined approach to efficiently establish the ground state pluripotency.

BackgroundDNA methylation at promoters is largely correlated with inhibition of gene expression. However, the role of DNA methylation at enhancers is not fully understood, although a crosstalk with chromatin marks is expected. Actually, there exist contradictory reports about positive and negative correlations between DNA methylation and H3K4me1, a chromatin hallmark of enhancers.ResultsWe investigated the relationship between DNA methylation and active chromatin marks through genome-wide correlations, and found anti-correlation between H3K4me1 and H3K4me3 enrichment at low and intermediate DNA methylation loci. We hypothesized “seesaw” dynamics between H3K4me1 and H3K4me3 in the low and intermediate DNA methylation range, in which DNA methylation discriminates between enhancers and promoters, marked by H3K4me1 and H3K4me3, respectively. Low methylated regions are H3K4me3 enriched, while those with intermediate DNA methylation levels are progressively H3K4me1 enriched. Additionally, the enrichment of H3K27ac, distinguishing active from primed enhancers, follows a plateau in the lower range of the intermediate DNA methylation level, corresponding to active enhancers, and decreases linearly in the higher range of the intermediate DNA methylation. Thus, the decrease of the DNA methylation switches smoothly the state of the enhancers from a primed to an active state. We summarize these observations into a rule of thumb of one-out-of-three methylation marks: “In each genomic region only one out of these three methylation marks {DNA methylation, H3K4me1, H3K4me3} is high. If it is the DNA methylation, the region is inactive. If it is H3K4me1, the region is an enhancer, and if it is H3K4me3, the region is a promoter”. To test our model, we used available genome-wide datasets of H3K4 methyltransferases knockouts. Our analysis suggests that CXXC proteins, as readers of non-methylated CpGs would regulate the “seesaw” mechanism that focuses H3K4me3 to unmethylated sites, while being repulsed from H3K4me1 decorated enhancers and CpG island shores.ConclusionsOur results show that DNA methylation discriminates promoters from enhancers through H3K4me1-H3K4me3 seesaw mechanism, and suggest its possible function in the inheritance of chromatin marks after cell division. Our analyses suggest aberrant formation of promoter-like regions and ectopic transcription of hypomethylated regions of DNA. Such mechanism process can have important implications in biological process in where it has been reported abnormal DNA methylation status such as cancer and aging.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4353-7) contains supplementary material, which is available to authorized users.

The firefly bioluminescence reaction, which uses luciferin, Mg-ATP, and molecular oxygen to yield an electronically excited oxyluciferin, is carried out by luciferase and visible light is emitted. The bioluminescence color of firefly luciferases is determined by the luciferase structure and assay conditions. Among different beetle luciferases, those from Phrixothrix railroad worm emit either yellow or red bioluminescence colors. Sequence alignment analysis shows that the red-emitter luciferase from Phrixothrix hirtus has an additional Arg residue at 353, which is absent in firefly luciferases. We report here the construction and purification of a mutant at residue Arg 356 , which is not conserved in beetle luciferases. By insertion of an additional residue (Arg 356 ) using site-specific insertion mutagenesis in a green-emitter luciferase (Lampyris turkestanicus) the color of emitted light was changed to red and the optimum temperature of activity was also increased. Insertion of this Arg in an important flexible loop showed changes of the bioluminescence color and the luciferase reaction took place with relatively retention of its basic kinetic properties such as K m and relative activity. Comparison of native and mutant luciferases using homology modeling reveals a significant conformational change of the flexible loop in the red mutant. Movement of flexible loop brought about a new ionic interaction concomitant with a change in polarity of the emitter site, thereby leading to red emission. It is worthwhile to note that the increased optimum temperature and emission of red light might make mutant luciferase a suitable reporter for the study of gene expression and bioluminescence imaging.Luciferases are the enzymes that catalyze the light-emitting reactions in bioluminescent organisms. In beetles they catalyze a two-step oxidation of luciferin in the presence of ATP, Mg 2ϩ , and molecular oxygen to produce light, oxyluciferin, CO 2 , and AMP (1, 2).The bioluminescence color of fireflies has a wide range from green to red depending on the species: fireflies emit in the yellow-green light (3, 4), click beetles emit in the green-orange (4, 5), and railroad worms emit in a wide range from green to red (6, 7). Although chemical reaction catalyzed by all beetle luciferases and the substrate (luciferin) are identical, these variations in color of emission are still observed (8).One of the main basis for differences in the luciferases bioluminescence color is the property of the emitter in the microenvironment localized in the enzyme active site. The observed bioluminescence color of pH-sensitive luciferases (but not in click beetle and railroad worm luciferases) shifts to a red region in acidic medium (9, 10). Differences in bioluminescence color are also attributed to the luciferase structure (11, 12). The construction of chimeric proteins (13, 14) and site-directed and random mutagenesis studies have revealed some important residues and regions involved in bioluminescence color (8,11,13,14). Given these results, four...

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The maintenance of multi-cellular developed tissue depends on the proper cell production rate to replace the cells destroyed by the programmed process of cell death. The stem cell is the main source of producing cells in a developed normal tissue. It makes the stem cell the lead role in the scene of a fully formed developed tissue to fulfill its proper functionality. By focusing on the impact of stochasticity, here, we propose a computational model to reveal the internal mechanism of a stem cell, which generates the right proportion of different types of specialized cells, distribute them into their right position, and in the presence of intercellular reactions, maintain the organized structure in a homeostatic state. The result demonstrates that the spatial pattern could be harassed by the population geometries. Besides, it clearly shows that our model with progenitor cells able to recover the stem cell presence could retrieve the initial pattern appropriately in the case of injury. One of the fascinating outcomes of this project is demonstrating the contradictory roles of stochasticity. It breaks the proper boundaries of the initial spatial pattern in the population. While, on the flip side of the coin, it is the exact factor that provides the demanded non-genetic diversity in the tissue. The remarkable characteristic of the introduced model as the stem cells’ internal mechanism is that it could control the overall behavior of the population without need for any external factors.

The emergence of phenotypic diversity in a population of cells and their arrangement in space and time is one of the most fascinating features of living systems. In fact, understanding multicellularity is unthinkable without explaining the proximate and the ultimate causes of cell differentiation in time and space. Simpler forms of cell differentiation can be found in unicellular organisms, such as bacterial biofilm, where reversible cell differentiation results in phenotypically diverse populations. In this manuscript, we attempt to start with the simple case of reversible nongenetic phenotypic to construct a model of differentiation and pattern formation. Our model, which we refer to as noise-driven differentiation (NDD) model, is an attempt to consider the prevalence of noise in biological systems, alongside what is known about genetic switches and signaling, to create a simple model which generates spatiotemporal patterns from bottom-up. Our simulations indicate that the presence of noise in cells can lead to reversible differentiation and the addition of signaling can create spatiotemporal pattern.