Specific DNMT3C flanking sequence preferences facilitate methylation of young murine retrotransposons.

The DNA methyltransferase DNMT3C appeared as a duplication of the DNMT3B gene in muroids and is required for silencing of young retrotransposons in the male germline. Using specialized assay systems, we investigate the flanking sequence preferences of DNMT3C and observe characteristic preferences for cytosine at the -2 and -1 flank that are unique among DNMT3 enzymes. We identify two amino acids in the catalytic domain of DNMT3C (C543 and V547) that are responsible for the DNMT3C-specific flanking sequence preferences and evolutionary conserved in muroids. Reanalysis of published data shows that DNMT3C flanking preferences are consistent with genome-wide methylation patterns in mouse ES cells only expressing DNMT3C. Strikingly, we show that CpG sites with the preferred flanking sequences of DNMT3C are enriched in murine retrotransposons that were previously identified as DNMT3C targets. Finally, we demonstrate experimentally that DNMT3C has elevated methylation activity on substrates derived from these biological targets. Our data show that DNMT3C flanking sequence preferences match the sequences of young murine retrotransposons which facilitates their methylation. By this, our data provide mechanistic insights into the molecular co-evolution of repeat elements and (epi)genetic defense systems dedicated to maintain genomic stability in mammals

Mechanistic insights into Cytosine-N3 Methylation by DNA Methyltransferase DNMT3A

Recently, it has been discovered that different DNA-(cytosine C5)-methyltransferases including DNMT3A generate low levels of 3mC [Rosic et al. (2018), Nat. Genet., 50, 452-459]. This reaction resulted in the co-evolution of DNMTs and ALKB2 DNA repair enzymes, but its mechanism remained elusive. Here, we investigated the catalytic mechanism of DNMT3A for cytosine N3 methylation. We generated several DNMT3A variants with mutated catalytic residues and measured their activities in 5mC and 3mC generation by liquid chromatography linked to tandem mass spectrometry. Our data suggest that the methylation of N3 instead of C5 is caused by an inverted binding of the flipped cytosine target base into the active-site pocket of the DNA methyltransferase, which is partially compatible with the arrangement of catalytic amino acid residues. Given that all DNA-(cytosine C5)-methyltransferases have a common catalytic mechanism, it is likely that other enzymes of this class generate 3mC following the same mechanism

Cooperative DNA Binding and Protein/DNA Fiber Formation Increases the Activity of the Dnmt3a DNA Methyltransferase

The Dnmt3a DNA methyltransferase has been shown to bind cooperatively to DNA and to form large multimeric protein/DNA fibers.However, it has also been reported to methylate DNA in a processive manner, a property that is incompatible with protein/DNAfiber formation. We show here that the DNA methylation rate of Dnmt3a increases more than linearly with increasing enzymeconcentration on a long DNA substrate, but not on a short 30-mer oligonucleotide substrate. We also show that addition ofa catalytically inactive Dnmt3a mutant, which carries an amino acid exchange in the catalytic center, increases the DNA methylationrate by wild type Dnmt3a on the long substrate but not on the short one. In agreement with this finding, preincubation experimentsindicate that stable protein/DNA fibers are formed on the long, but not on the short substrate. In addition, methylation experimentswith substrates containing one or two CpG sites did not provide evidence for a processive mechanism over a wide range of enzymeconcentrations. These data clearly indicate that Dnmt3a binds to DNA in a cooperative reaction and that the formation of stableprotein/DNA fibers increases the DNA methylation rate. Fiber formation occurs at low μm concentrations of Dnmt3a, which are in the range of Dnmt3a concentrations in the nucleus of embryonic stem cells. Understandingthe mechanism of Dnmt3a is of vital importance because Dnmt3a is a hotspot of somatic cancer mutations one of which has beenimplicated in changing Dnmt3a processivity

Purification and Characterization of Recombinant Expressed Apple Allergen Mal d 1

Mal d 1 is the primary apple allergen in northern Europe. To explain the differences in the allergenicity of apple varieties, it is essential to study its properties and interaction with other phytochemicals, which might modulate the allergenic potential. Therefore, an optimized production route followed by an unsophisticated purification step for Mal d 1 and respective mutants is desired to produce sufficient amounts. We describe a procedure for the transformation of the plasmid in competent E. coli cells, protein expression and rapid one-step purification. r-Mal d 1 with and without a polyhistidine-tag are purified by immobilized metal ion affinity chromatography (IMAC) and fast-protein liquid chromatography (FPLC) using a high-resolution anion-exchange column, respectively. Purity is estimated by SDS-PAGE using an image-processing program (Fiji). For both mutants an appropriate yield of r-Mal d 1 with purity higher than 85% is achieved. The allergen is characterized after tryptic in gel digestion by peptide analyses using HPLC-MS/MS. Secondary structure elements are calculated based on CD-spectroscopy and the negligible impact of the polyhistidine-tag on the folding is confirmed. The formation of dimers is proved by mass spectrometry and reduction by DTT prior to SDS-PAGE. Furthermore, the impact of the freeze and thawing process, freeze drying and storage on dimer formation is investigated

A Stochastic Model for the Formation of Spatial Methylation Patterns

DNA methylation is an epigenetic mechanism whose important role in development has been widely recognized. This epigenetic modification results in heritable changes in gene expression not encoded by the DNA sequence. The underlying mechanisms controlling DNA methylation are only partly understood and recently different mechanistic models of enzyme activities responsible for DNA methylation have been proposed. Here we extend existing Hidden Markov Models (HMMs) for DNA methylation by describing the occurrence of spatial methylation patterns over time and propose several models with different neighborhood dependencies. We perform numerical analysis of the HMMs applied to bisulfite sequencing measurements and accurately predict wild-type data. In addition, we find evidence that the enzymes' activities depend on the left 5' neighborhood but not on the right 3' neighborhood.Comment: 18 pages, 7 figures, content of former appendix now included in the main part; accepted by 15th International Conference on Computational Methods in Systems Biology (CMSB), 201