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8-OxoG in GC-rich Sp1 binding sites enhances gene transcription during adipose tissue development in juvenile mice [RNA-Seq]

ABSTRACT: We observed that transcriptional activity and the number of active genes were significantly correlated with the distribution of 8-oxoG in gene promoter regions, as determined by liquid chromatography/mass spectrometry (LC/MS), and 8-oxoG and RNA sequencing

ORGANISM(S): Mus musculus

PROVIDER: GSE124359 | GEO | 2019/06/30

REPOSITORIES: GEO

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8-OxoG in GC-rich Sp1 binding sites enhances gene transcription during adipose tissue development in juvenile mice [8oxoG-seq]

Project description:We observed that transcriptional activity and the number of active genes were significantly correlated with the distribution of 8-oxoG in gene promoter regions, as determined by liquid chromatography/mass spectrometry (LC/MS), and 8-oxoG and RNA sequencing

2019-06-30 | GSE124712 | GEO

8-OxoG in GC-rich Sp1 binding sites enhances gene transcription in adipose tissue of juvenile mice.

Project description:The oxidation of guanine to 8-oxoguanine (8-oxoG) is the most common type of oxidative DNA lesion. There is a growing body of evidence indicating that 8-oxoG is not only pre-mutagenic, but also plays an essential role in modulating gene expression along with its cognate repair proteins. In this study, we investigated the relationship between 8-oxoG formed under intrinsic oxidative stress conditions and gene expression in adipose and lung tissues of juvenile mice. We observed that transcriptional activity and the number of active genes were significantly correlated with the distribution of 8-oxoG in gene promoter regions, as determined by reverse-phase liquid chromatography/mass spectrometry (RP-LC/MS), and 8-oxoG and RNA sequencing. Gene regulation by 8-oxoG was not associated with the degree of 8-oxoG formation. Instead, genes with GC-rich transcription factor binding sites in their promoters became more active with increasing 8-oxoG abundance as also demonstrated by specificity protein 1 (Sp1)- and estrogen response element (ERE)-luciferase assays in human embryonic kidney (HEK293T) cells. These results indicate that the occurrence of 8-oxoG in GC-rich Sp1 binding sites is important for gene regulation during adipose tissue development.

| S-EPMC6821754 | biostudies-literature

Dysregulation of acrosome formation network by 8-oxoguanine (8-oxoG) in infertile sperm

Project description:Various environmental factors contribute to dysregulated spermatogenic gene network, abnormal spermatogenesis, and eventually impaired sperm fertility. 8-hydroxyguanine (8-oxoG) is the most common and well-studied oxidative DNA lesion of the four DNA bases and unrepaired 8-oxoG modifications are associated with DNA fragmentation in sperms. However, the molecular effects of 8-oxoG generated in sperm DNA by oxidative stress on spermatogenesis are not entirely understood. Here, we identified one infertile Korean native striped cattle at 6-year old (C14) due to asthenozoospermia and teratozoospermia. We compared global concentration of 8-oxoG by reverse-phase liquid chromatography/mass spectrometry (RP-LC/MS), the genomic distribution of 8-oxoG by next-generation sequencing (OG-seq), and expression of sperm proteins by 2-dimensional electrophoresis followed by mass spectrometry (2D/MS) in sperms of C14 with those of normal counterpart (C13). We found that averaged levels of 8-oxoG in C13 and C14 sperms were 0.027% and 0.044% of total dG and 8-oxoG was significantly greater in infertile sperm DNA (p = 0.0028). More than 81% of the 8-oxoG loci were distributed around the transcription start site (TSS) and 8-oxoG harboring 165 genes, including phospholipases, were annotated exclusively into infertile sperm DNA. Gene set enrichment analysis (GSEA) and the protein-protein interaction networking revealed that the Golgi apparatus was significantly enriched with the 8-oxoG genes of infertile sperm (q = 2.20E-07). Proteomic analysis verified that acrosome-related proteins including Acrosin-binding protein (ACRBP) and Sperm equatorial segment protein 1 (SPESP1) were 1.6-fold and 2.6-fold down-regulated in infertile sperm, respectively. These results suggest that 8-oxoG formation during spermatogenesis would dysregulate the acrosome-related gene network, causing structural and functional defects of sperm, leading to infertility.

2021-06-30 | GSE165538 | GEO

8-OxoG in GC-rich Sp1 binding sites enhances gene transcription during adipose tissue development in juvenile mice

Project description:This SuperSeries is composed of the SubSeries listed below.

2019-06-30 | GSE124713 | GEO

8-OxoG in GC-rich Sp1 binding sites enhances gene transcription during adipose tissue development in juvenile mice

Project description:8-OxoG in GC-rich Sp1 binding sites enhances gene transcription during adipose tissue development in juvenile mice

| PRJNA513196 | ENA

8-OxoG in GC-rich Sp1 binding sites enhances gene transcription during adipose tissue development in juvenile mice [RNA-Seq]

Project description:8-OxoG in GC-rich Sp1 binding sites enhances gene transcription during adipose tissue development in juvenile mice [RNA-Seq]

| PRJNA511834 | ENA

8-OxoG in GC-rich Sp1 binding sites enhances gene transcription during adipose tissue development in juvenile mice [8oxoG-seq]

Project description:8-OxoG in GC-rich Sp1 binding sites enhances gene transcription during adipose tissue development in juvenile mice [8oxoG-seq]

| PRJNA513197 | ENA

Identification of 8-oxoG binding proteins in Deinococcus radiodurans

Project description:8-oxo-7,8-dihydroguanine (8-oxoG) is a common RNA oxidation that has been implicated in carcinogenesis, neurodegeneration, and aging. Some? Many? RNA-binding proteins have shown binding preference for 8-oxoG modified RNA; such binding? can protect cells from oxidative stress. To date, the presence of specific 8-oxoG-recognizing proteins is only known in model organisms, but, how these proteins cooperate is still unclear. Here, we use RNA affinity chromatography and mass spectrometry to search for proteins that specifically bind 8-oxoG-modified RNA in Deinococcus radiodurans, an extremophilic bacterium with extraordinary resistance to oxidative stresses. We identified four proteins that selectively bind to oxidized RNA: polynucleotide phosphorylase (DR_2063/PNPase), ATP-dependent DEAD-box RNA helicase (DR_0335/RhlB), ribosomal protein S1 (DR_1983/RpsA), and transcriptional termination factor (DR_1338/Rho). The knockout of PNPase and RhlB in D. radiodurans caused increased sensitivity to hydrogen peroxide and a significant accumulation of 8-oxoG modified RNA. Importantly, PNPase directly interacts with RhlB in D. radiodurans; however, no additional phenotypic effect was observed for the double deletion of pnp and rhlB compared to the individual single deletions. Overall, our findings suggest a role of the PNPase-RhlB complex in targeting 8-oxoG-modified RNAs for rapid degradation and thereby constitutes an important component of D. radiodurans resistance to oxidative stress.

2022-07-10 | PXD028861 | Pride

Identification of targets of the protein disulfide reductase thioredoxin

Project description:Identification of targets of the protein disulfide reductase thioredoxin using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and thiol specific differential labeling with isotope-coded affinity tags (ICAT). Reduction of specific target disulfides is quantified by measuring ratios of cysteine residues labeled with the heavy (13C) and light (12C) ICAT reagents in peptides derived from tryptic digests of Trx-treated and non-treated samples. Keywords: protein, LC-MS/MS, ICAT

2008-11-20 | GSE11650 | GEO

YangziChen2024 - Metabolic Machine Learning Predictor Model for Diagnosis of Gastric Cancer

Project description:The paper "Metabolomic Machine Learning Predictor for Diagnosis and Prognosis of Gastric Cancer" addresses the need for non-invasive diagnostic tools for gastric cancer (GC). Traditional methods like endoscopy are invasive and expensive. The authors conducted a targeted metabolomics analysis of 702 plasma samples to develop machine learning models for GC diagnosis and prognosis. The diagnostic model, using 10 metabolites, achieved a sensitivity of 0.905, outperforming conventional protein marker-based methods. The prognostic model effectively stratified patients into risk groups, surpassing traditional clinical models. I have successfully reproduced the diagnosis model from the paper. This machine learning-based system differentiates GC patients from non-GC controls using metabolomics data from plasma samples analyzed by liquid chromatography-mass spectrometry (LC-MS). The model focuses on 10 metabolites, including succinate, uridine, lactate, and serotonin. Employing LASSO regression and a random forest classifier, the model achieved an AUROC of 0.967, with a sensitivity of 0.854 and specificity of 0.926. This model significantly outperforms traditional diagnostic methods and underscores the potential of integrating machine learning with metabolomics for early GC detection and treatment.

2024-07-23 | MODEL2407230001 | BioModels

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