Mark the transition: chromatin modifications and cell fate decision

Lactate-induced histone lactylation by p300 promotes osteoblast differentiation

Lactate, which is synthesized as an end product by lactate dehydrogenase A (LDHA) from pyruvate during anaerobic glycolysis, has attracted attention for its energy metabolism and oxidant effects. A novel histone modification-mediated gene regulation mechanism termed lactylation by lactate was recently discovered. The present study examined the involvement of histone lactylation in undifferentiated cells that underwent differentiation into osteoblasts. C2C12 cells cultured in medium with a high glucose content (4500 mg/L) showed increases in marker genes (Runx2, Sp7, Tnap) indicating BMP-2-induced osteoblast differentiation and ALP staining activity, as well as histone lactylation as compared to those cultured in medium with a low glucose content (900 mg/L). Furthermore, C2C12 cells stimulated with the LDH inhibitor oxamate had reduced levels of BMP-2-induced osteoblast differentiation and histone lactylation, while addition of lactate to C2C12 cells cultured in low glucose medium resulted in partial restoration of osteoblast differentiation and histone lactylation. These results indicate that lactate synthesized by LDHA during glucose metabolism is important for osteoblast differentiation of C2C12 cells induced by BMP-2. Additionally, silencing of p300, a possible modifier of histone lactylation, also inhibited osteoblast differentiation and reduced histone lactylation. Together, these findings suggest a role of histone lactylation in promotion of undifferentiated cells to undergo differentiation into osteoblasts.

Epigenetic modifications and their relation to caste and sex determination and adult division of labor in the stingless bee Melipona scutellaris

Stingless bees of the genus Melipona, have long been considered an enigmatic case among social insects for their mode of caste determination, where in addition to larval food type and quantity, the genotype also has a saying, as proposed over 50 years ago by Warwick E. Kerr. Several attempts have since tried to test his Mendelian two-loci/two-alleles segregation hypothesis, but only recently a single gene crucial for sex determination in bees was evidenced to be sex-specifically spliced and also caste-specifically expressed in a Melipona species. Since alternative splicing is frequently associated with epigenetic marks, and the epigenetic status plays a major role in setting the caste phenotype in the honey bee, we investigated here epigenetic chromatin modification in the stingless bee Melipona scutellaris. We used an ELISA-based methodology to quantify global methylation status and western blot assays to reveal histone modifications. The results evidenced DNA methylation/demethylation events in larvae and pupae, and significant differences in histone methylation and phosphorylation between newly emerged adult queens and workers. The epigenetic dynamics seen in this stingless bee species represent a new facet in the caste determination process in Melipona bees and suggest a possible mechanism that is likely to link a genotype component to the larval diet and adult social behavior of these bees.

Simultaneously learning DNA motif along with its position and sequence rank preferences through expectation maximization algorithm

Although de novo motifs can be discovered through mining over-represented sequence patterns, this approach misses some real motifs and generates many false positives. To improve accuracy, one solution is to consider some additional binding features (i.e., position preference and sequence rank preference). This information is usually required from the user. This article presents a de novo motif discovery algorithm called SEME (sampling with expectation maximization for motif elicitation), which uses pure probabilistic mixture model to model the motif's binding features and uses expectation maximization (EM) algorithms to simultaneously learn the sequence motif, position, and sequence rank preferences without asking for any prior knowledge from the user. SEME is both efficient and accurate thanks to two important techniques: the variable motif length extension and importance sampling. Using 75 large-scale synthetic datasets, 32 metazoan compendium benchmark datasets, and 164 chromatin immunoprecipitation sequencing (ChIP-Seq) libraries, we demonstrated the superior performance of SEME over existing programs in finding transcription factor (TF) binding sites. SEME is further applied to a more difficult problem of finding the co-regulated TF (coTF) motifs in 15 ChIP-Seq libraries. It identified significantly more correct coTF motifs and, at the same time, predicted coTF motifs with better matching to the known motifs. Finally, we show that the learned position and sequence rank preferences of each coTF reveals potential interaction mechanisms between the primary TF and the coTF within these sites. Some of these findings were further validated by the ChIP-Seq experiments of the coTFs. The application is available online.