Methyl Hyperplaniate

Methylation at DNA, RNA and protein levels plays critical roles in many cellular processes and is associated with diverse differentiation events, physiological activities and human diseases. To aid in the diagnostic and therapeutic design for cancer treatment utilising methylation, this review provides a boutique yet comprehensive overview on methylation at different levels including the mechanisms, cross-talking and clinical implications with a particular focus on cancers. We conclude that DNA methylation is the sole type of methylation that has been largely translated into clinics and used for, mostly, early diagnosis. Translating the onco-therapeutic and prognostic values of RNA and protein methylations into clinical use deserves intensive efforts. Simultaneous examination of methylations at multiple levels or together with other forms of molecular markers represents an interesting research direction with profound clinical translational potential.

Mercury (Hg) methylation, methylmercury (MeHg) demethylation, and inorganic redox transformations of Hg are microbe-mediating processes that determine the fate and cycling of Hg and MeHg in many environments, and by doing so influence the health of humans and wild life. The discovery of the Hg methylation genes, hgcAB, in the last decade together with advances in high throughput and genome sequencing methods, have resulted in an expanded appreciation of the diversity of Hg methylating microbes. This review aims to describe experimentally confirmed and recently discovered hgcAB gene-carrying Hg methylating microbes; phylogenetic and taxonomic analyses are presented. In addition, the current knowledge on transformation mechanisms, the organisms that carry them out, and the impact of environmental parameters on Hg methylation, MeHg demethylation, and inorganic Hg reduction and oxidation is summarized. This knowledge provides a foundation for future action toward mitigating the impact of environmental Hg pollution.

Protein arginine (R) methylation is a post-translational modification involved in various biological processes, such as RNA splicing, DNA repair, immune response, signal transduction, and tumor development. Although several advancements were made in the study of this modification by mass spectrometry, researchers still face the problem of a high false discovery rate. We present a dataset of high-quality methylations obtained from several different heavy methyl stable isotope labeling with amino acids in cell culture experiments analyzed with a machine learning-based tool and show that this model allows for improved high-confidence identification of real methyl-peptides. Overall, our results are consistent with the notion that protein R methylation modulates protein-RNA interactions and suggest a role in rewiring protein-protein interactions, for which we provide experimental evidence for a representative case (i.e., NONO [non-POU domain-containing octamer-binding protein]-paraspeckle component 1 [PSPC1]). Upon intersecting our R-methyl-sites dataset with the PhosphoSitePlus phosphorylation dataset, we observed that R methylation correlates differently with S/T-Y phosphorylation in response to various stimuli. Finally, we explored the application of heavy methyl stable isotope labeling with amino acids in cell culture to identify unconventional methylated residues and successfully identified novel histone methylation marks on serine 28 and threonine 32 of H3. The database generated, named ProMetheusDB, is freely accessible at https://bioserver.ieo.it/shiny/app/prometheusdb.