Whole-Genome Bisulfite Sequencing Protocol for the Analysis of Genome-Wide DNA Methylation and Hydroxymethylation Patterns at Single-Nucleotide Resolution.

The analysis of genome-wide epigenomic alterations including DNA methylation and hydroxymethylation has become a subject of intensive research for many biological and clinical questions. DNA methylation analysis bears the particular promise to supplement or replace biochemical and imaging-based tests for the next generation of personalized medicine. Whole-genome bisulfite sequencing (WGBS) using next-generation sequencing technologies is currently considered the gold standard for a comprehensive and quantitative analysis of DNA methylation throughout the genome. However, bisulfite conversion does not allow distinguishing between cytosine methylation and hydroxymethylation requiring an additional chemical or enzymatic step to identify hydroxymethylated cytosines. Here, we provide a detailed protocol based on a commercial kit for the preparation of sequencing libraries for the comprehensive whole-genome analysis of DNA methylation and/or hydroxymethylation. The protocol is based on the construction of sequencing libraries from limited amounts of input DNA by ligation of methylated adaptors to the fragmented DNA prior to bisulfite conversion. For analyses requiring a quantitative distinction between 5-methylcytosine and 5-hydroxymethylcytosines levels, an oxidation step is included in the same workflow to perform oxidative bisulfite sequencing (OxBs-Seq). In this case, two sequencing libraries will be generated and sequenced: a classic methylome following bisulfite conversion and analyzing modified cytosines (not distinguishing between methylated and hydroxymethylated cytosines) and a methylome analyzing only methylated cytosines, respectively. Hydroxymethylation levels are deduced from the differences between the two reactions. We also provide a step-by-step description of the data analysis using publicly available bioinformatic tools. The described protocol has been successfully applied to different human and plant samples and yields robust and reproducible results.

Rockfish: A transformer-based model for accurate 5-methylcytosine prediction from nanopore sequencing.

DNA methylation plays an important role in various biological processes, including cell differentiation, ageing, and cancer development. The most important methylation in mammals is 5-methylcytosine mostly occurring in the context of CpG dinucleotides. Sequencing methods such as whole-genome bisulfite sequencing successfully detect 5-methylcytosine DNA modifications. However, they suffer from the serious drawbacks of short read lengths and might introduce an amplification bias. Here we present Rockfish, a deep learning algorithm that significantly improves read-level 5-methylcytosine detection by using Nanopore sequencing. Rockfish is compared with other methods based on Nanopore sequencing on R9.4.1 and R10.4.1 datasets. There is an increase in the single-base accuracy and the F1 measure of up to 5 percentage points on R.9.4.1 datasets, and up to 0.82 percentage points on R10.4.1 datasets. Moreover, Rockfish shows a high correlation with whole-genome bisulfite sequencing, requires lower read depth, and achieves higher confidence in biologically important regions such as CpG-rich promoters while being computationally efficient. Its superior performance in human and mouse samples highlights its versatility for studying 5-methylcytosine methylation across varied organisms and diseases. Finally, its adaptable architecture ensures compatibility with new versions of pores and chemistry as well as modification types.

Bioinspired Heterocoordination in Adaptable Cobalt Metal-Organic Framework for DNA Epigenetic Modification Detection.

Metal-organic frameworks (MOFs) show unique advantages in simulating the dynamics and fidelity of natural coordination. Inspired by zinc finger protein, a second linker was introduced to affect the homogeneous MOF system and thus facilitate the emergence of diverse functionalities. Under the systematic identification of 12 MOF species (i.e., metal ions, linkers) and 6 second linkers (trigger), a dissipative system consisting of Co-BDC-NO2 and o-phenylenediamine (oPD) was screened out, which can rapidly and in situ generate a high photothermal complex (η = 36.9%). Meanwhile, both the carboxylation of epigenetic modifications and metal ion (Fe3+, Ni2+, Cu2+, Zn2+, Co2+ and Mn2+) screening were utilized to improve the local coordination environment so that the adaptable Co-MOF growth on the DNA strand was realized. Thus, epigenetic modification information on DNA was converted to an amplified metal ion signal, and then oPD was further introduced to generate bimodal dissipative signals by which a simple, high-sensitivity detection strategy of 5-hydroxymethylcytosine (LOD = 0.02%) and 5-formylcytosine (LOD = 0.025‰) was developed. The strategy provides one low-cost method (< 0.01 $/sample) for quantifying global epigenetic modifications, which greatly promotes epigenetic modification-based early disease diagnosis. This work also proposes a general heterocoordination design concept for molecular recognition and signal transduction, opening a new MOF-based sensing paradigm.

Effective training of nanopore callers for epigenetic marks with limited labelled data.

Nanopore sequencing platforms combined with supervised machine learning (ML) have been effective at detecting base modifications in DNA such as 5-methylcytosine (5mC) and N6-methyladenine (6mA). These ML-based nanopore callers have typically been trained on data that span all modifications on all possible DNA [Formula: see text]-mer backgrounds-a complete training dataset. However, as nanopore technology is pushed to more and more epigenetic modifications, such complete training data will not be feasible to obtain. Nanopore calling has historically been performed with hidden Markov models (HMMs) that cannot make successful calls for [Formula: see text]-mer contexts not seen during training because of their independent emission distributions. However, deep neural networks (DNNs), which share parameters across contexts, are increasingly being used as callers, often outperforming their HMM cousins. It stands to reason that a DNN approach should be able to better generalize to unseen [Formula: see text]-mer contexts. Indeed, herein we demonstrate that a common DNN approach (DeepSignal) outperforms a common HMM approach (Nanopolish) in the incomplete data setting. Furthermore, we propose a novel hybrid HMM-DNN approach, amortized-HMM, that outperforms both the pure HMM and DNN approaches on 5mC calling when the training data are incomplete. This type of approach is expected to be useful for calling other base modifications such as 5-hydroxymethylcytosine and for the simultaneous calling of different modifications, settings in which complete training data are not likely to be available.

MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models.

RNA modification serves as a pivotal component in numerous biological processes. Among the prevalent modifications, 5-methylcytosine (m5C) significantly influences mRNA export, translation efficiency and cell differentiation and are also associated with human diseases, including Alzheimer's disease, autoimmune disease, cancer, and cardiovascular diseases. Identification of m5C is critically responsible for understanding the RNA modification mechanisms and the epigenetic regulation of associated diseases. However, the large-scale experimental identification of m5C present significant challenges due to labor intensity and time requirements. Several computational tools, using machine learning, have been developed to supplement experimental methods, but identifying these sites lack accuracy and efficiency. In this study, we introduce a new predictor, MLm5C, for precise prediction of m5C sites using sequence data. Briefly, we evaluated eleven RNA sequence-derived features with four basic machine learning algorithms to generate baseline models. From these 44 models, we ranked them based on their performance and subsequently stacked the Top 20 baseline models as the best model, named MLm5C. The MLm5C outperformed the-state-of-the-art predictors. Notably, the optimization of the sequence length surrounding the modification sites significantly improved the prediction performance. MLm5C is an invaluable tool in accelerating the detection of m5C sites within the human genome, thereby facilitating in the characterization of their roles in post-transcriptional regulation.

DGA-5mC: A 5-methylcytosine site prediction model based on an improved DenseNet and bidirectional GRU method.

The 5-methylcytosine (5mC) in the promoter region plays a significant role in biological processes and diseases. A few high-throughput sequencing technologies and traditional machine learning algorithms are often used by researchers to detect 5mC modification sites. However, high-throughput identification is laborious, time-consuming and expensive; moreover, the machine learning algorithms are not so advanced. Therefore, there is an urgent need to develop a more efficient computational approach to replace those traditional methods. Since deep learning algorithms are more popular and have powerful computational advantages, we constructed a novel prediction model, called DGA-5mC, to identify 5mC modification sites in promoter regions by using a deep learning algorithm based on an improved densely connected convolutional network (DenseNet) and the bidirectional GRU approach. Furthermore, we added a self-attention module to evaluate the importance of various 5mC features. The deep learning-based DGA-5mC model algorithm automatically handles large proportions of unbalanced data for both positive and negative samples, highlighting the model's reliability and superiority. So far as the authors are aware, this is the first time that the combination of an improved DenseNet and bidirectional GRU methods has been used to predict the 5mC modification sites in promoter regions. It can be seen that the DGA-5mC model, after using a combination of one-hot coding, nucleotide chemical property coding and nucleotide density coding, performed well in terms of sensitivity, specificity, accuracy, the Matthews correlation coefficient (MCC), area under the curve and Gmean in the independent test dataset: 90.19%, 92.74%, 92.54%, 64.64%, 96.43% and 91.46%, respectively. In addition, all datasets and source codes for the DGA-5mC model are freely accessible at https://github.com/lulukoss/DGA-5mC.

Substrate DNA length regulates the activity of TET 5-methylcytosine dioxygenases.

The ten-eleven translocation (TET) isoforms (TET1-3) play critical roles in epigenetic transcription regulation. In addition, mutations in the TET2 gene are frequently detected in patients with glioma and myeloid malignancies. TET isoforms can oxidize 5-methylcytosine to 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxylcytosine, by iterative oxidation. The in vivo DNA demethylation activity of TET isoforms may depend on many factors including enzyme's structural features, its interaction with DNA-binding proteins, chromatin context, DNA sequence, DNA length, and configuration. The rationale for this study is to identify the preferred DNA length and configuration in the substrates of TET isoforms. We have used a highly sensitive LC-MS/MS-based method to compare the substrate preference of TET isoforms. To this end, four DNA substrate sets (S1, S2, S3, S4) of different sequences were chosen. In addition, in each set, four different lengths of DNA substrates comprising 7-, 13-, 19-, and 25-mer nucleotides were synthesized. Each DNA substrate was further used in three different configurations, that is, double stranded symmetrically-methylated, double stranded hemi-methylated, and single stranded single-methylated to evaluate their effect on TET-mediated 5mC oxidation. We demonstrate that mouse TET1 (mTET1) and human TET2 (hTET2) have highest preference for 13-mer dsDNA substrates. Increasing or decreasing the length of dsDNA substrate reduces product formation. In contrast to their dsDNA counterparts, the length of ssDNA substrates did not have a predictable effect on 5mC oxidation. Finally, we show that substrate specificity of TET isoforms correlates with their DNA binding efficiency. Our results demonstrate that mTET1 and hTET2 prefer 13-mer dsDNA as a substrate over ssDNA. These results may help elucidate novel properties of TET-mediated 5mC oxidation and help develop novel diagnostic tools to detect TET2 function in patients.

Selective Functionalisation of 5-Methylcytosine by Organic Photoredox Catalysis.

The epigenetic modification 5-methylcytosine plays a vital role in development, cell specific gene expression and disease states. The selective chemical modification of the 5-methylcytosine methyl group is challenging. Currently, no such chemistry exists. Direct functionalisation of 5-methylcytosine would improve the detection and study of this epigenetic feature. We report a xanthone-photosensitised process that introduces a 4-pyridine modification at a C(sp3 )-H bond in the methyl group of 5-methylcytosine. We propose a reaction mechanism for this type of reaction based on density functional calculations and apply transition state analysis to rationalise differences in observed reaction efficiencies between cyanopyridine derivatives. The reaction is initiated by single electron oxidation of 5-methylcytosine followed by deprotonation to generate the methyl group radical. Cross coupling of the methyl radical with 4-cyanopyridine installs a 4-pyridine label at 5-methylcytosine. We demonstrate use of the pyridination reaction to enrich 5-methylcytosine-containing ribonucleic acid.

im5C-DSCGA: A Proposed Hybrid Framework Based on Improved DenseNet and Attention Mechanisms for Identifying 5-methylcytosine Sites in Human RNA.

BACKGROUND: 5-methylcytosine (m5C) is a key post-transcriptional modification that plays a critical role in RNA metabolism. Owing to the large increase in identified m5C modification sites in organisms, their epigenetic roles are becoming increasingly unknown. Therefore, it is crucial to precisely identify m5C modification sites to gain more insight into cellular processes and other mechanisms related to biological functions. Although researchers have proposed some traditional computational methods and machine learning algorithms, some limitations still remain. In this study, we propose a more powerful and reliable deep-learning model, im5C-DSCGA, to identify novel RNA m5C modification sites in humans. METHODS: Our proposed im5C-DSCGA model uses three feature encoding methods initially-one-hot, nucleotide chemical property (NCP), and nucleotide density (ND)-to extract the original features in RNA sequences and ensure splicing; next, the original features are fed into the improved densely connected convolutional network (DenseNet) and Convolutional Block Attention Module (CBAM) mechanisms to extract the advanced local features; then, the bidirectional gated recurrent unit (BGRU) method is used to capture the long-term dependencies from advanced local features and extract global features using Self-Attention; Finally, ensemble learning is used and full connectivity is used to classify and predict the m5C site. RESULTS: Unsurprisingly, the deep-learning-based im5C-DSCGA model performed well in terms of sensitivity (Sn), specificity (SP), accuracy (Acc), Matthew's correlation coefficient (MCC), and area under the curve (AUC), generating values of 81.0%, 90.8%, 85.9%, 72.1%, and 92.6%, respectively, in the independent test dataset following the use of three feature encoding methods. CONCLUSIONS: We critically evaluated the performance of im5C-DSCGA using five-fold cross-validation and independent testing and compared it to existing methods. The MCC metric reached 72.1% when using the independent test, which is 3.0% higher than the current state-of-the-art prediction method Deepm5C model. The results show that the im5C-DSCGA model achieves more accurate and stable performances and is an effective tool for predicting m5C modification sites. To the authors' knowledge, this is the first time that the improved DenseNet, BGRU, CBAM Attention mechanism, and Self-Attention mechanism have been combined to predict novel m5C sites in human RNA.

Recent Advances on DNA Base Flipping: A General Mechanism for Writing, Reading, and Erasing DNA Modifications.

The modification of DNA bases is a classic hallmark of epigenetics. Four forms of modified cytosine-5-methylcytosine, 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxylcytosine-have been discovered in eukaryotic DNA. In addition to cytosine carbon-5 modifications, cytosine and adenine methylated in the exocyclic amine-N4-methylcytosine and N6-methyladenine-are other modified DNA bases discovered even earlier. Each modified base can be considered a distinct epigenetic signal with broader biological implications beyond simple chemical changes. Since 1994, several crystal structures of proteins and enzymes involved in writing, reading, and erasing modified bases have become available. Here, we present a structural synopsis of writers, readers, and erasers of the modified bases from prokaryotes and eukaryotes. Despite significant differences in structures and functions, they are remarkably similar regarding their engagement in flipping a target base/nucleotide within DNA for specific recognitions and/or reactions. We thus highlight base flipping as a common structural framework broadly applied by distinct classes of proteins and enzymes across phyla for epigenetic regulations of DNA.

Structure and Function of TET Enzymes.

Mammalian DNA methylation mainly occurs at the carbon-C5 position of cytosine (5mC). TET enzymes were discovered to successively oxidize 5mC to 5-hydromethylcytosine (5hmC), 5-formylcytosine (5fC), and 5-carboxylcytosine (5caC). Ten-eleven translocation (TET) enzymes and oxidized 5mC derivatives play important roles in various biological and pathological processes, including regulation of DNA demethylation, gene transcription, embryonic development, and oncogenesis. In this chapter, we will discuss the discovery of TET-mediated 5mC oxidation and the structure, function, and regulation of TET enzymes. We start with brief descriptions of the mechanisms of TET-mediated 5mC oxidation and TET-dependent DNA demethylation. We then discuss the TET-mediated epigenetic reprogramming in pluripotency maintenance and embryogenesis, as well as in tumorigenesis and neural system. We further describe the structural basis for substrate recognition and preference in TET-mediated 5mC oxidation. Finally, we summarize the chemical molecules and interacting proteins that regulate TET's activity.

An improved residual network using deep fusion for identifying RNA 5-methylcytosine sites.

MOTIVATION: 5-Methylcytosine (m5C) is a crucial post-transcriptional modification. With the development of technology, it is widely found in various RNAs. Numerous studies have indicated that m5C plays an essential role in various activities of organisms, such as tRNA recognition, stabilization of RNA structure, RNA metabolism and so on. Traditional identification is costly and time-consuming by wet biological experiments. Therefore, computational models are commonly used to identify the m5C sites. Due to the vast computing advantages of deep learning, it is feasible to construct the predictive model through deep learning algorithms. RESULTS: In this study, we construct a model to identify m5C based on a deep fusion approach with an improved residual network. First, sequence features are extracted from the RNA sequences using Kmer, K-tuple nucleotide frequency component (KNFC), Pseudo dinucleotide composition (PseDNC) and Physical and chemical property (PCP). Kmer and KNFC extract information from a statistical point of view. PseDNC and PCP extract information from the physicochemical properties of RNA sequences. Then, two parts of information are fused with new features using bidirectional long- and short-term memory and attention mechanisms, respectively. Immediately after, the fused features are fed into the improved residual network for classification. Finally, 10-fold cross-validation and independent set testing are used to verify the credibility of the model. The results show that the accuracy reaches 91.87%, 95.55%, 92.27% and 95.60% on the training sets and independent test sets of Arabidopsis thaliana and M.musculus, respectively. This is a considerable improvement compared to previous studies and demonstrates the robust performance of our model. AVAILABILITY AND IMPLEMENTATION: The data and code related to the study are available at https://github.com/alivelxj/m5c-DFRESG.

Evolved DNA Duplex Readers for Strand-Asymmetrically Modified 5-Hydroxymethylcytosine/5-Methylcytosine CpG Dyads.

5-Methylcytosine (mC) and 5-hydroxymethylcytosine (hmC), the two main epigenetic modifications of mammalian DNA, exist in symmetric and asymmetric combinations in the two strands of CpG dyads. However, revealing such combinations in single DNA duplexes is a significant challenge. Here, we evolve methyl-CpG-binding domains (MBDs) derived from MeCP2 by bacterial cell surface display, resulting in the first affinity probes for hmC/mC CpGs. One mutant has low nanomolar affinity for a single hmC/mC CpG, discriminates against all 14 other modified CpG dyads, and rivals the selectivity of wild-type MeCP2. Structural studies indicate that this protein has a conserved scaffold and recognizes hmC and mC with two dedicated sets of residues. The mutant allows us to selectively address and enrich hmC/mC-containing DNA fragments from genomic DNA backgrounds. We anticipate that this novel probe will be a versatile tool to unravel the function of hmC/mC marks in diverse aspects of chromatin biology.

5-methylcytosine modification by Plasmodium NSUN2 stabilizes mRNA and mediates the development of gametocytes.

5-methylcytosine (m5C) is an important epitranscriptomic modification involved in messenger RNA (mRNA) stability and translation efficiency in various biological processes. However, it remains unclear if m5C modification contributes to the dynamic regulation of the transcriptome during the developmental cycles of Plasmodium parasites. Here, we characterize the landscape of m5C mRNA modifications at single nucleotide resolution in the asexual replication stages and gametocyte sexual stages of rodent (Plasmodium yoelii) and human (Plasmodium falciparum) malaria parasites. While different representations of m5C-modified mRNAs are associated with the different stages, the abundance of the m5C marker is strikingly enhanced in the transcriptomes of gametocytes. Our results show that m5C modifications confer stability to the Plasmodium transcripts and that a Plasmodium ortholog of NSUN2 is a major mRNA m5C methyltransferase in malaria parasites. Upon knockout of P. yoelii nsun2 (pynsun2), marked reductions of m5C modification were observed in a panel of gametocytogenesis-associated transcripts. These reductions correlated with impaired gametocyte production in the knockout rodent malaria parasites. Restoration of the nsun2 gene in the knockout parasites rescued the gametocyte production phenotype as well as m5C modification of the gametocytogenesis-associated transcripts. Together with the mRNA m5C profiles for two species of Plasmodium, our findings demonstrate a major role for NSUN2-mediated m5C modifications in mRNA transcript stability and sexual differentiation in malaria parasites.

m5C-Atlas: a comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome.

5-Methylcytosine (m5C) is one of the most prevalent covalent modifications on RNA. It is known to regulate a broad variety of RNA functions, including nuclear export, RNA stability and translation. Here, we present m5C-Atlas, a database for comprehensive collection and annotation of RNA 5-methylcytosine. The database contains 166 540 m5C sites in 13 species identified from 5 base-resolution epitranscriptome profiling technologies. Moreover, condition-specific methylation levels are quantified from 351 RNA bisulfite sequencing samples gathered from 22 different studies via an integrative pipeline. The database also presents several novel features, such as the evolutionary conservation of a m5C locus, its association with SNPs, and any relevance to RNA secondary structure. All m5C-atlas data are accessible through a user-friendly interface, in which the m5C epitranscriptomes can be freely explored, shared, and annotated with putative post-transcriptional mechanisms (e.g. RBP intermolecular interaction with RNA, microRNA interaction and splicing sites). Together, these resources offer unprecedented opportunities for exploring m5C epitranscriptomes. The m5C-Atlas database is freely accessible at https://www.xjtlu.edu.cn/biologicalsciences/m5c-atlas.

Integrated single-cell sequencing of 5-hydroxymethylcytosine and genomic DNA using scH&G-seq.

The asymmetric distribution of 5-hydroxymethylcytosine (5hmC) between two DNA strands of a chromosome enables endogenous reconstruction of cellular lineages at an individual-cell-division resolution. Further, when integrated with data on genomic variants to infer clonal lineages, this combinatorial information accurately reconstructs larger lineage trees. Here, we provide a detailed protocol for single-cell 5-hydroxymethylcytosine and genomic DNA sequencing (scH&G-seq) to simultaneously quantify 5hmC and genomic DNA from the same cell to reconstruct lineage trees at a single-cell-division resolution. For complete details on the use and execution of this protocol, please refer to Wangsanuwat et al., 2021.

The Impact of the HydroxyMethylCytosine epigenetic signature on DNA structure and function.

We present a comprehensive, experimental and theoretical study of the impact of 5-hydroxymethylation of DNA cytosine. Using molecular dynamics, biophysical experiments and NMR spectroscopy, we found that Ten-Eleven translocation (TET) dioxygenases generate an epigenetic variant with structural and physical properties similar to those of 5-methylcytosine. Experiments and simulations demonstrate that 5-methylcytosine (mC) and 5-hydroxymethylcytosine (hmC) generally lead to stiffer DNA than normal cytosine, with poorer circularization efficiencies and lower ability to form nucleosomes. In particular, we can rule out the hypothesis that hydroxymethylation reverts to unmodified cytosine physical properties, as hmC is even more rigid than mC. Thus, we do not expect dramatic changes in the chromatin structure induced by differences in physical properties between d(mCpG) and d(hmCpG). Conversely, our simulations suggest that methylated-DNA binding domains (MBDs), associated with repression activities, are sensitive to the substitution d(mCpG) ➔ d(hmCpG), while MBD3 which has a dual activation/repression activity is not sensitive to the d(mCpG) d(hmCpG) change. Overall, while gene activity changes due to cytosine methylation are the result of the combination of stiffness-related chromatin reorganization and MBD binding, those associated to 5-hydroxylation of methylcytosine could be explained by a change in the balance of repression/activation pathways related to differential MBD binding.

Interaction of Thymine DNA Glycosylase with Oxidised 5-Methyl-cytosines in Their Amino- and Imino-Forms.

Thymine DNA Glycosylase (TDG) is an enzyme of the base excision repair mechanism and removes damaged or mispaired bases from DNA via hydrolysis of the glycosidic bond. Specificity is of high importance for such a glycosylase, so as to avoid the damage of intact DNA. Among the substrates reported for TDG are mispaired uracil and thymine but also formyl-cytosine and carboxyl-cytosine. Methyl-cytosine and hydroxylmethyl-cytosine are, in contrast, not processed by the TDG enzyme. We have in this work employed molecular dynamics simulations to explore the conformational dynamics of DNA carrying a formyl-cytosine or carboxyl-cytosine and compared those to DNA with the non-cognate bases methyl-cytosine and hydroxylmethyl-cytosine, as amino and imino tautomers. Whereas for the mispairs a wobble conformation is likely decisive for recognition, all amino tautomers of formyl-cytosine and carboxyl-cytosine exhibit the same Watson-Crick conformation, but all imino tautomers indeed form wobble pairs. The conformational dynamics of the amino tautomers in free DNA do not exhibit differences that could be exploited for recognition, and also complexation to the TDG enzyme does not induce any alteration that would indicate preferable binding to one or the other oxidised methyl-cytosine. The imino tautomers, in contrast, undergo a shift in the equilibrium between a closed and a more open, partially flipped state, towards the more open form upon complexation to the TDG enzyme. This stabilisation of the more open conformation is most pronounced for the non-cognate bases methyl-cytosine and hydroxyl-cytosine and is thus not a likely mode for recognition. Moreover, calculated binding affinities for the different forms indicate the imino forms to be less likely in the complexed DNA. These findings, together with the low probability of imino tautomers in free DNA and the indifference of the complexed amino tautomers, suggest that discrimination of the oxidised methyl-cytosines does not take place in the initial complex formation.

Functional succinate dehydrogenase deficiency is a common adverse feature of clear cell renal cancer.

Reduced succinate dehydrogenase (SDH) activity resulting in adverse succinate accumulation was previously considered relevant only in 0.05 to 0.5% of kidney cancers associated with germline SDH mutations. Here, we sought to examine a broader role for SDH loss in kidney cancer pathogenesis/progression. We report that underexpression of SDH subunits resulting in accumulation of oncogenic succinate is a common feature in clear cell renal cell carcinoma (ccRCC) (∼80% of all kidney cancers), with a marked adverse impact on survival in ccRCC patients (n = 516). We show that SDH down-regulation is a critical brake in the TCA cycle during ccRCC pathogenesis and progression. In exploring mechanisms of SDH down-regulation in ccRCC, we report that Von Hippel-Lindau loss-induced hypoxia-inducible factor-dependent up-regulation of miR-210 causes direct inhibition of the SDHD transcript. Moreover, shallow deletion of SDHB occurs in ∼20% of ccRCC. We then demonstrate that SDH loss-induced succinate accumulation contributes to adverse loss of 5-hydroxymethylcytosine, gain of 5-methylcytosine, and enhanced invasiveness in ccRCC via inhibition of ten-eleven translocation (TET)-2 activity. Intriguingly, binding affinity between the catalytic domain of recombinant TET-2 and succinate was found to be very low, suggesting that the mechanism of succinate-induced attenuation of TET-2 activity is likely via product inhibition rather than competitive inhibition. Finally, exogenous ascorbic acid, a TET-activating demethylating agent, led to reversal of the above oncogenic effects of succinate in ccRCC cells. Collectively, our study demonstrates that functional SDH deficiency is a common adverse feature of ccRCC and not just limited to the kidney cancers associated with germline SDH mutations.

TET-Like Oxidation in 5-Methylcytosine and Derivatives: A Computational and Experimental Study.

The epigenetic marker 5-methylcytosine (5mC) is an important factor in DNA modification and epigenetics. It can be modified through a three-step oxidation performed by ten-eleven-translocation (TET) enzymes and we have previously reported that the iron(IV)-oxo complex [Fe(O)(Py5 Me2 H)]2+ (1) can oxidize 5mC. Here, we report the reactivity of this iron(IV)-oxo complex towards a wider scope of methylated cytosine and uracil derivatives relevant for synthetic DNA applications, such as 1-methylcytosine (1mC), 5-methyl-iso-cytosine (5miC) and thymine (T/5mU). The observed kinetic parameters are corroborated by calculation of the C-H bond energies at the reactive sites which was found to be an efficient tool for reaction rate prediction of 1 towards methylated DNA bases. We identified oxidation products of methylated cytosine derivatives using HPLC-MS and GC-MS. Thereby, we shed light on the impact of the methyl group position and resulting C-H bond dissociation energies on reactivity towards TET-like oxidation.