Structural basis for DNMT3A-mediated de novo DNA methylation.

DNA methylation by de novo DNA methyltransferases 3A (DNMT3A) and 3B (DNMT3B) at cytosines is essential for genome regulation and development. Dysregulation of this process is implicated in various diseases, notably cancer. However, the mechanisms underlying DNMT3 substrate recognition and enzymatic specificity remain elusive. Here we report a 2.65-ångström crystal structure of the DNMT3A-DNMT3L-DNA complex in which two DNMT3A monomers simultaneously attack two cytosine-phosphate-guanine (CpG) dinucleotides, with the target sites separated by 14 base pairs within the same DNA duplex. The DNMT3A-DNA interaction involves a target recognition domain, a catalytic loop, and DNMT3A homodimeric interface. Arg836 of the target recognition domain makes crucial contacts with CpG, ensuring DNMT3A enzymatic preference towards CpG sites in cells. Haematological cancer-associated somatic mutations of the substrate-binding residues decrease DNMT3A activity, induce CpG hypomethylation, and promote transformation of haematopoietic cells. Together, our study reveals the mechanistic basis for DNMT3A-mediated DNA methylation and establishes its aetiological link to human disease

Temporal dynamic effects of meteorological factors and air quality on the physical health of the older adults in Shenzhen, China

IntroductionMeteorological and environmental factors can affect people’s lives and health, which is crucial among the older adults. However, it is currently unclear how they specifically affect the physical condition of older adults people.MethodsWe collected and analyzed the basic physical examination indicators of 41 older adults people for two consecutive years (2021 and 2022), and correlated them with meteorological and environmental factors. Partial correlation was also conducted to exclude unrelated factors as well.ResultsWe found that among the physical examination indicators of the older adults for two consecutive years, five indicators (HB, WBC, HbAlc, CB, LDL-C) showed significant differences across the population, and they had significantly different dynamic correlation patterns with six meteorological (air pressure, temperature, humidity, precipitation, wind speed, and sunshine duration) and seven air quality factors (NO2, SO2, PM10, O3-1h, O3-8h, CO, PM2.5).DiscussionOur study has discovered for the first time the dynamic correlation between indicators in normal basic physical examinations and meteorological factors and air quality indicators, which will provide guidance for the future development of policies that care for the healthy life of the older adults

Quantitative Assessment of Arsenite-Induced Perturbation of Ubiquitinated Proteome.

Arsenic contamination in food and groundwater constitutes a public health concern for more than 200 million people worldwide. Individuals chronically exposed to arsenic through drinking and ingestion exhibit a higher risk of developing cancers and cardiovascular diseases. Nevertheless, the underlying mechanisms of arsenic toxicity are not fully understood. Arsenite is known to bind to and deactivate RING finger E3 ubiquitin ligases; thus, we reason that a systematic interrogation about how arsenite exposure modulates global protein ubiquitination may reveal novel molecular targets for arsenic toxicity. By employing liquid chromatography-tandem mass spectrometry, in combination with stable isotope labeling by amino acids in cell culture (SILAC) and immunoprecipitation of di-glycine-conjugated lysine-containing tryptic peptides, we assessed the alterations in protein ubiquitination in GM00637 human skin fibroblast cells upon arsenite exposure at the entire proteome level. We observed that arsenite exposure led to altered ubiquitination of many proteins, where the alterations in a large majority of ubiquitination events are negatively correlated with changes in expression of the corresponding proteins, suggesting their modulation by the ubiquitin-proteasomal pathway. Moreover, we observed that arsenite exposure confers diminished ubiquitination of a rate-limiting enzyme in cholesterol biosynthesis, HMGCR, at Lys248. We also revealed that TRC8 is the major E3 ubiquitin ligase for HMGCR ubiquitination in HEK293T cells, and the arsenite-induced diminution of HMGCR ubiquitination is abrogated upon genetic depletion of TRC8. In summary, we systematically characterized arsenite-induced perturbations in a ubiquitinated proteome in human cells and found that the arsenite-elicited attenuation of HMGCR ubiquitination in HEK293T cells involves TRC8

Facile Enzymatic Synthesis of Base J-Containing Oligodeoxyribonucleotides and an Analysis of the Impact of Base J on DNA Replication in Cells

<div><p>We reported here the use of T4 bacteriophage β-glucosyltransferase (T4 β-GT) for the facile synthesis of base J-containing oligodeoxyribonucleotides (ODNs). We found that the enzyme could catalyze the glucosylation of 5-hydroxymethyl-2-deoxyuridine (5hmU) in both single- and double-stranded ODNs, though the latter reaction occurred only when 5hmU was mispaired with a guanine. In addition, base J blocked moderately DNA replication, but it did not induce mutations during replication in human cells.</p></div

<i>In-vivo</i> replication studies of base J and 5hmU in HEK293T cells.

<p>(A) Experimental procedures for determining the effects of 5hmU and base J on DNA replication in cells. (B) Representative PAGE gel image showing the restriction fragments. (C) The bypass efficiencies of base J and 5hmU in HEK293T cells. The data represent the mean and standard deviation of results from three independent replication experiments.</p

Chemical Structures of 2′-deoxynucleosides containing 5hmU, 5hmC, base J and Glc-5hmC.

<p>Chemical Structures of 2′-deoxynucleosides containing 5hmU, 5hmC, base J and Glc-5hmC.</p

ESI-MS and MS/MS characterizations of d(ATGGCGJGCTAT) (‘J’ represents base J): (A) Negative-ion ESI-MS; (B) The product-ion spectrum of the [M–3H]^3– ion (<i>m/z</i> 1283.8).

<p>ESI-MS and MS/MS characterizations of d(ATGGCGJGCTAT) (‘J’ represents base J): (A) Negative-ion ESI-MS; (B) The product-ion spectrum of the [M–3H]^3– ion (<i>m/z</i> 1283.8).</p

Effects of Tet-induced oxidation products of 5-methylcytosine on Dnmt1- and DNMT3a-mediated cytosine methylation

We investigated systematically the effects of Tet-induced oxidation products of 5-methylcytosine on Dnmt1- and DNMT3a-mediated cytosine methylation in synthetic duplex DNA. We found that the replacement of 5-methylcytosine at a CpG site with a 5-hydroxymethylcytosine, 5-formylcytosine, 5-carboxylcytosine or 5-hydroxymethyluracil resulted in altered methylation of cytosine at both the opposite and the neighboring CpG sites. Our results provided important new knowledge about the implications of the 5-methylcytosine oxidation products in maintenance cytosine methylation

Arsenite Binds to ZNF598 to Perturb Ribosome-Associated Protein Quality Control.

Arsenic pollution in drinking water is a widespread public health problem, and it affects approximately 200 million people in over 70 countries. Many human diseases, including neurodegenerative disorders, are engendered by the malfunction of proteins involved in important biological processes and are elicited by protein misfolding and/or loss of protein quality control during translation. Arsenic exposure results in proteotoxic stress, though the detailed molecular mechanisms remain poorly understood. Here, we showed that arsenite interacts with ZNF598 protein in cells and exposure of human skin fibroblasts to arsenite results in significant decreases in the ubiquitination levels of lysine residues 138 and 139 in RPS10 and lysine 8 in RPS20, which are regulatory post-translational modifications important in ribosome-associated protein quality control. Furthermore, the arsenite-elicited diminutions in ubiquitinations of RPS10 and RPS20 gave rise to augmented read-through of poly(adenosine)-containing stalling sequences, which was abolished in ZNF598 knockout cells. Together, our study revealed a novel mechanism underlying the arsenic-induced proteostatic stress in human cells

Deep learning based transformer fault signal recognition algorithm

Abstract： In view of the complex structure and high maintenance cost of transformers, this paper proposes a transformer fault signal recognition algorithm based on deep learning. Firstly, the voiceprint signal under the working condition of the transformer is analyzed and the two-dimensional image signal is converted. Based on the advantages of VGG16 neural network in the image, a MCA attention mechanism is proposed, which can retain both background information and detail information. Secondly it optimizes the maximum pooled down sampling in VGG16, and adopts a soft pooled sampling method to reduce the feature loss caused by the maximum pooled down sampling in the image. Finally, in order to avoid the occurrence of over fitting, the activation function in the top structure of VGG16 is optimized, and the SELU activation function that can be self normalized is quoted. The experiment proves that the generalized S-transform is the best choice for converting one-dimensional time-domain signal to two-dimensional image signal, and the average recognition rate of the proposed algorithm for six types of fault signals reaches 99.15%