Kyoto Encyclopedia Of Genes And Genomes Pathway Research Articles

QTL mapping and transcriptome analysis of seed germination under PEG-induced water stress in Lactuca spp.

The impact of limited water availability on lettuce growth has been well documented. However, the mechanisms by which lettuce controls seed germination under water stress remain unknown. Germination percentage was evaluated in the cv. Salinas (Lactuca sativa) (L. sativa) × US96UC23 (Lactuca serriola) (L. serriola) recombinant inbred line (RIL) population and USDA germplasm collection using 10% polyethylene glycol (PEG). About 50% of both populations displayed less than 90% germination. The average broad-sense heritability (H2) for germination percentage was 0.81 across both populations. Two quantitative trait loci (QTL) for germination percentage were identified on chromosomes 4 and 8 in the RIL population. The RNA-Seq and network analyses of wild lettuce, US96UC23, were performed using the control (distilled water, dH2O) and treatment (10% PEG) datasets. The number of differentially expressed genes (DEGs) was 4,095. The top 20 gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were assessed by enrichment analysis. The consensus network analysis captured 44 modules. Gene networks were constructed for the top 20 hub genes in 10 significant modules from each dataset. This study comprehensively explains QTL, GO terms, KEGG pathways, and gene networks associated with lettuce seed germination under osmotic stress.

A NETWORK PHARMACOLOGY-BASED DRUG REPURPOSING STUDY OF LEVETIRACETAM UNCOVERS ITS INTERACTION WITH MULTI-DRUG TARGETS IN PARKINSON'S DISEASE

Objective: The current study utilized network pharmacology to examine how Levetiracetam interacts with specific drug targets associated with Parkinson's Disease (PD) treatment. Methods: We used information from Kyoto Encyclopedia of Genes and Genome (KEGG) studies and Protein-Protein Interaction (PPI) pathway analysis to create a network that depicts the relationships between Levetiracetam and PD targets. Further investigation involved PPI analysis, molecular docking, and Molecular Dynamics (MD) simulation studies, ultimately pinpointing five protein targets. Their participation in pathways such as Ribonucleic acid Polymerase II-specific Deoxyribonucleic acid binding Transcription Factor Binding (Gene Ontology [GO]:0061629), Axon (GO: 0030424), and Excitatory Postsynaptic Potential was emphasized by GO and KEGG pathway enrichment. Additionally, Dopamine Receptor D2 (DRD2), Solute Carrier Family 6 Member 3 (SLC6A3), Glycogen Synthase Kinase 3 Beta (GSK3B), Poly (ADP-ribose) Polymerase 1 (PARP1) and Myeloperoxidase (MPO) were identified as protein targets through PPI and molecular docking analysis. Results: The results of molecular docking showed that protein targets, SLC6A3, have highest binding affinity with Levetiracetam. The MD Simulation result of Levetiracetam-SLC6A3 docked complex represented the complex to be quite stable with few conformational changes in the SLC6A3 structure. DRD2, SLC6A3, GSK3B, PARP1, MPO were recognized as the likely protein targets of Levetiracetam for treating PD. SLC6A3 was considered as a target of Levetiracetam in PD. Conclusion: Our study revealed the mechanism of Levetiracetam in the treatment of PD and can contribute to more effective treatment for the same. By identifying key protein targets, this research lays the groundwork for future studies that could further explore Levetiracetam’s efficacy.

Genome-wide methylation and transcriptome differential analysis of skeletal muscle in broilers with valgus-varus deformity

ABSTRACT 1. Valgus-varus deformity (VVD) is a disease that severely affects leg function in broilers and for which there is no effective control method current available. Although DNA methylation has an important impact on most physiological and pathological processes, its involvement in skeletal muscle growth and development in VVD broilers is unknown. In this study, genome-wide DNA methylation was analysed in VVD-affected and normal broilers using whole genome resulphite sequencing. 2. The results showed that in the cytosine-phosphoric acid-guanine (CG) sequence environment there was a methylation rate of about 55% and 4,265 differentially methylated regions (DMRs) were found in the CG. Of these, 550 were located in the promoter, 547 in the exon region, and 1,718 in the intron region. 3. All differentially methylated genes (DMGs) were analysed for enrichment of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The GO was enriched in pathways related to protein degradation such as proteasome complex, endopeptidase complex and extracellular region. The KEGG pathways were enriched in signalling pathways related to protein degradation and catabolism such as proteasome, nitrogen metabolism, adherens junction and alanine. 4. Protein interactions analysis revealed that FOS, MYL9, and FRAS1 had a high degree of interactions, in which the DNA methylation level of the MYL9 promoter region was negatively correlated with mRNA expression level. Further studies showed that 5-azacytidine (5-AzaC) inhibited DNMT1 and DNMT3A gene expression and promoted MYL9 expression. 5. This study systematically investigated overall DNA methylation patterns in the leg muscle of VVD and normal broilers. It screened common differential genes in conjunction with transcriptomic data to further identify genes associated with muscle growth and development. This study provides new insights to better understand the pathogenesis of VVD from an epigenetic perspective.

Identification of key genes in diabetic nephropathy based on lipid metabolism.

Diabetic nephropathy (DN) is a common systemic microvascular complication of diabetes with a high incidence rate. Notably, the disturbance of lipid metabolism is associated with DN progression. The present study aimed to identify lipid metabolism-related hub genes associated with DN for improved diagnosis of DN. The gene expression profile data of DN and healthy samples (GSE142153) were obtained from the Gene Expression Omnibus database, and the lipid metabolism-related genes were obtained from the Molecular Signatures Database. Differentially expressed genes (DEGs) between DN and healthy samples were analyzed. The weighted gene co-expression network analysis (WGCNA) was performed to examine the relationship between genes and clinical traits to identify the key module genes associated with DN. Next, the Venn Diagram R package was used to identify the lipid metabolism-related genes associated with DN and their protein-protein interaction (PPI) network was constructed. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. The hub genes were identified using machine-learning algorithms. The Gene Set Enrichment Analysis (GSEA) was used to analyze the functions of the hub genes. The present study also investigated the immune infiltration discrepancies between DN and healthy samples, and assessed the correlation between the immune cells and hub genes. Finally, the expression levels of key genes were verified by reverse transcription-quantitative (RT-q)PCR. The present study determined 1,445 DEGs in DN samples. In addition, 694 DN-related genes in MEyellow and MEturquoise modules were identified by WGCNA. Next, the Venn Diagram R package was used to identify 17 lipid metabolism-related genes and to construct a PPI network. GO analysis revealed that these 17 genes were markedly associated with 'phospholipid biosynthetic process' and 'cholesterol biosynthetic process', while the KEGG analysis showed that they were enriched in 'glycerophospholipid metabolism' and 'fatty acid degradation'. In addition, SAMD8 and CYP51A1 were identified through the intersections of two machine-learning algorithms. The results of GSEA revealed that the 'mitochondrial matrix' and 'GTPase activity' were the markedly enriched GO terms in both SAMD8 and CYP51A1. Their KEGG pathways were mainly concentrated in the 'pathways of neurodegeneration-multiple diseases'. Immune infiltration analysis showed that nine types of immune cells had different expression levels in DN (diseased) and healthy samples. Notably, SAMD8 and CYP51A1 were both markedly associated with activated B cells and effector memory CD8 T cells. Finally, RT-qPCR confirmed the high expression of SAMD8 and CYP51A1 in DN. In conclusion, lipid metabolism-related genes SAMD8 and CYP51A1 may play key roles in DN. The present study provides fundamental information on lipid metabolism that may aid the diagnosis and treatment of DN.

Integrative Bioinformatics and Experimental Analysis of Curcumin's Role in Regulating Ferroptosis to Combat Osteoporosis

This study utilized bioinformatics and data mining techniques to explore the molecular mechanism of curcumin in treating osteoporosis (OP) through the lens of ferroptosis, thereby identifying novel therapeutic targets. The datasets GSE35958, GSE35956, GSE7429, and GSE7158 were obtained from the Gene Expression Omnibus (GEO) database. GSE35958 and GSE35956 were employed as training sets for data integration, while GSE7429 and GSE7158 served as independent validation sets. Through retrieval from the FerrDb database, iron death-related genes (FRGs) were identified, and the differentially expressed genes (DEGs) were intersected to obtain differentially expressed FRGs (DEFRGs). Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted, followed by the construction of a Protein-Protein Interaction (PPI) network to identify Hub genes. The DGIdb database was utilized to predict candidate drugs associated with the Hub genes, and molecular docking and in vitro experiments confirmed that curcumin targets the Hub genes EGFR and PTGS2.Through in vitro testing of curcumin on BMSC cells, researchers examined cell vitality, iron death, osteogenic differentiation, mineralization, and the impact on EGFR and PTGS2 levels. The analysis yielded 2212 DEGs, 484 FRGs, with 45 FDEGs at the intersection. GO analysis revealed involvement in regulating mitochondrial proteins, amino acid transport across plasma membranes, and protein ubiquitination. KEGG pathway analysis indicated associations with iron death, FoxO signaling, mTOR signaling, cell aging, osteoclast differentiation, and GSH metabolism. Utilizing the MCC algorithm, five Hub genes were identified: MAPK3, PTGS2, TGFB1, CYBB, and EGFR, showing diagnostic potential for iron death. Curcumin displayed affinity for EGFR and PTGS2, mitigating iron-induced effects on BMSCs such as increased reactive oxygen species, Fe3+ levels, and decreased mitochondrial membrane potential. Furthermore, curcumin reversed these effects, suggesting EGFR and PTGS2 as targets for curcumin to inhibit BMSC ferroptosis and potentially delay osteoporosis development. Maintaining iron homeostasis and targeting BMSC ferroptosis could offer therapeutic avenues for iron overload-induced osteoporosis.

Non-coding RNA alterations in occlusal disharmony-induced anxiety-like behaviour.

Occlusal disharmony (OD) may induce anxiety-like behaviours; however, the underlying mechanism remains unclear. Herein, we explored the expression profiles of non-coding RNAs (ncRNAs), along with their biological function and regulatory network, in anxiety-like behaviour induced by OD. Occlusal disharmony was produced by anterior crossbite of C57BL/6 mice. Behavioural tests, corticosterone (CORT) and serotonin (5-HT) levels were used to measure anxiety. In addition, RNA sequencing was used to screen all differentially expressed (DE) ncRNAs. Moreover, the RNA-binding proteins interacting with ncRNAs were predicted by the ENCORI database and confirmed using western blots. The significant differences in behavioural tests and CORT suggested the successful induction of anxiety-like behaviour by OD. In OD mice, ncRNAs were significantly dysregulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses suggested that the DE ncRNAs were enriched in anxiety-related pathways. CircRNA10039 was upregulated, and PTBP1 was predicted to interact with circRNA10039. In addition, KEGG pathway analysis showed that PTBP1 may be associated with messenger RNA biogenesis and spliceosomes. OD induced by anterior crossbite can lead to the anxiety-like behaviours. During this process, ncRNA also changes. CircRNA10039 and PTBP1 may play a role in OD-induced anxiety-like behaviours.

Unveiling the efficacy and mechanism of Danggui-Shaoyao-San in treating nephrotic syndrome: A meta-analysis and network pharmacology study

Aim of the studyThe purpose of this study was to investigate the efficacy and mechanism of DSS in treating nephrotic syndrome through meta-analysis and network pharmacology methods. Materials and methodsTo conduct a comprehensive search for randomized controlled trials on the efficacy of Danggui Shaoyao San (DSS) in the treatment of nephrotic syndrome, we searched across eight electronic databases from their establishment to May 1, 2023. The Cochrane Collaboration's Risk of Bias 2 tool was used to evaluate the quality of evidence regarding bias risk and outcomes. Statistical analysis was performed using RevMan software (version 5.4). Furthermore, network pharmacology was employed to validate the underlying mechanism. ResultsThis study included 14 articles that involved 1256 patients with nephrotic syndrome. The clinical efficacy of DSS against nephrotic syndrome was significantly higher than that of Western medical treatment alone. In comparison with the control groups, which were administered Western medicines alone, the use of DSS significantly increased plasma albumin levels (mean difference [MD] = 4.32, 95 % confidence interval [CI] [2.37, 6.24], p < 0.00001) and reduced 24 h urinary protein excretion (MD = −0.92, 95 % CI [−1.11, −0.73], p < 0.00001), total cholesterol levels (MD = −1.23, 95 % CI [−1.76, −0.70], p < 0.00001), triglyceride levels (MD = −0.37, 95 % CI [−0.54, −0.20], p < 0.00001). Furthermore, the combination of DSS with Western medicines achieved better control of adverse reactions in comparison with the control groups (relative risk = 0.37, 95 % CI [0.29, 0.49], p < 0.00001). Network pharmacology analysis identified 39 important active compounds and 18 core target genes involved in the treatment of primary nephrotic syndrome by DSS. Gene Ontology enrichment analysis identified 2126 biological processes, 64 cellular components, and 115 molecular functions, while Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis identified 149 signaling pathways. Key active compounds include ginsenoside Rg5, ginsenoside Rg1, schisandrin A, berberine, gallic acid, quercetin, and β-sitosterol, while potential core target genes include IL6, AKT1, TNF, VEGFA, IL1B, and TP53. KEGG pathway analysis indicated that DSS is involved in multiple mechanisms, such as neural development, synaptic plasticity, programmed cell death, inflammation, and immunity. ConclusionsDSS has higher efficacy and safety in the treatment of nephrotic syndrome and acts on nephrotic syndrome via mechanisms that involve multiple targets, components, and pathways.

Identification and validation of autophagy-related genes in Hirschsprung's disease.

Hirschsprung's disease (HSCR) is a congenital disorder characterized by aganglionosis in the intermuscular and submucosal nerve plexuses of the gut, leading to impaired gastrointestinal function. Although the precise cause and pathophysiology of HSCR remain elusive, increasing evidence points to a significant role of autophagy in its development, warranting further investigation into its underlying mechanisms. This study utilized publicly available microarray expression profiling datasets, GSE96854 and GSE98502, from the Gene Expression Omnibus (GEO). The R software (version 4.2.0) was employed to identify autophagy-related genes potentially showing differential expression in HSCR. Subsequent analyses included correlation analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein interaction (PPI) network analysis using the STRING database (version 11.0) and Cytoscape software (version 3.8.2). Ultimately, HSCR samples were used to verify the mRNA levels of important genes by quantitative real-time polymerase chain reaction (qRT-PCR) in a laboratory setting. We have discovered 20 genes that are involved in autophagy and show variable expression. Among these genes, 15 are up-regulated and five are down-regulated. The enrichment analysis using the GO and KEGG pathways revealed a notable enrichment in pathways related to the control of autophagy. Nine hub genes were found via the investigation of the PPI network constructed from STRING database and module analysis using Cytoscape. Moreover, the concordance between SIRT1 expression in the HSCR model and the bioinformatics analysis of mRNA chip findings was validated using qRT-PCR. Utilizing bioinformatics analysis, we identified 20 potential genes associated with Hirschsprung's disease that play a role in autophagy. Notably, the upregulation of SIRT1 may profoundly influence the progression of HSCR by regulating autophagy-related pathways, offering a novel perspective on the disease's pathogenesis.

Predicting the Pathway Involvement of All Pathway and Associated Compound Entries Defined in the Kyoto Encyclopedia of Genes and Genomes

Background/Objectives: Predicting the biochemical pathway involvement of a compound could facilitate the interpretation of biological and biomedical research. Prior prediction approaches have largely focused on metabolism, training machine learning models to solely predict based on metabolic pathways. However, there are many other types of pathways in cells and organisms that are of interest to biologists. Methods: While several publications have made use of the metabolites and metabolic pathways available in the Kyoto Encyclopedia of Genes and Genomes (KEGG), we downloaded all the compound entries with pathway annotations available in the KEGG. From these data, we constructed a dataset where each entry contained features representing compounds combined with features representing pathways, followed by a binary label indicating whether the given compound is associated with the given pathway. We trained multi-layer perceptron binary classifiers on variations of this dataset. Results: The models trained on 6485 KEGG compounds and 502 pathways scored an overall mean Matthews correlation coefficient (MCC) performance of 0.847, a median MCC of 0.848, and a standard deviation of 0.0098. Conclusions: This performance on all 502 KEGG pathways represents a roughly 6% improvement over the performance of models trained on only the 184 KEGG metabolic pathways, which had a mean MCC of 0.800 and a standard deviation of 0.021. These results demonstrate the capability to effectively predict biochemical pathways in general, in addition to those specifically related to metabolism. Moreover, the improvement in the performance demonstrates additional transfer learning with the inclusion of non-metabolic pathways.

Changes in the expression profile of serum lncRNAs in pregnant women with high hepatitis B viral load during antiviral and non-antiviral treatment

ObjectiveThis research analyzes the potential of long non-coding RNAs (lncRNAs) as markers in determining the necessity of antiviral treatment in pregnant women by examining alterations in the expression profile of serum lncRNAs in pregnant women with elevated hepatitis B viral load (HBVL) under antiviral and non-antiviral treatment regimens between the second trimester and delivery.MethodsSerum was obtained from 6 s-trimester pregnant women with high HBVL and no intrauterine infection. Then, 3 of these women were randomly selected for antiviral treatment, with the remaining 3 women undergoing non-antiviral treatment as control. Serum samples were again collected from these 6 women before delivery. The expression profile of lncRNAs was analyzed with microarray technology, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The axes of hub lncRNA-miRNA-mRNA were identified based on the competing endogenous RNA (ceRNA) network.ResultsThe expression profile of serum lncRNAs in pregnant women with high HBVL changed significantly from the second trimester of pregnancy until delivery under antiviral or non-antiviral treatment. The Venn diagram was utilized to screen out the jointly up-regulated and down-regulated lncRNAs in the serum of pregnant women under antiviral and non-antiviral treatment before delivery. Additionally, the KEGG pathway enrichment analysis results showed that lncRNAs might mediate the Hippo pathway in HBV infection. Based on the ceRNA network, 3 hub lncRNAs (CATG00000076041.1, LINC01310, and G014655) were found to potentially regulate the key gene TP73 in the Hippo pathway.ConclusionIn this study, we retrieved co-differentially expressed lncRNAs in pregnant women with high HBVL under antiviral or non-antiviral treatment, which may be used as markers for evaluating whether pregnant women with high HBVL may be free of antiviral treatment. This study may provide a basis for preventing potential adverse effects of antiviral treatment on maternal and fetal health.

Serum proteomic analysis identified ITIH4 as a potential novel biomarker for feline infectious peritonitis

Feline infectious peritonitis (FIP) is a fatal feline disease. At present, the reference standard for FIP diagnosis is immunohistochemistry (IHC) of organs, but this method involves high time-related costs, invasive sampling procedures and professional requirements. Serological detection is a common auxiliary method for diagnosing diseases. As a result, we assessed the changes in the serum proteome of FIP patients with the aim of identifying novel specific serum biomarkers that could aid in the clinical diagnosis of FIP. Pre- and postinfection groups were compared and 92 differentially expressed proteins (DEPs) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEPs revealed that the enriched GO terms and KEGG pathways among the DEPs were immune activation, peptidase regulator activity and the complement and coagulation cascade pathways. The level of peptidase regulator interalpha-trypsin inhibitor heavy chain 4 (ITIH4) in cat serum was significantly correlated with FIP. The areas under the ROC curve (AUCs) of full-length ITIH4 (f-ITIH4) and cleaved ITIH4 (c-ITIH4) expression were 0.922 and 1.000, respectively, which allowed the discrimination of FIP cats from healthy cats. These results suggest that ITIH4 may be a potential serum biomarker for detecting early FIP. SignificanceFIP causes fatal disease in cats of almost all ages, and there is currently no effective vaccine or treatment for FIP. Therefore, early diagnosis is extremely important for disease prevention and control. The results of the model and clinical samples revealed that ITIH4 was significantly increased in the serum of FIP cats. This study is the first to propose ITIH4 as a diagnostic biomarker in cats with FIP and our results suggest that serum ITIH4 levels might identify cats with FIP during the early stage.

Exploring the predictive values of SERP4 and FRZB in dilated cardiomyopathy based on an integrated analysis

Background and objectiveThe aim of this study was to investigate potential hub genes for dilated cardiomyopathy (DCM).MethodsFive DCM-related microarray datasets were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were used for identification. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, disease ontology, gene ontology annotation and protein-protein interaction (PPI) network analysis were then performed, while a random forest was constructed to explore central genes. Artificial neural networks were used to compare with known genes and to develop new diagnostic models. 240 population blood samples were collected and expression of hub genes was verified in these samples using RT-PCR and demonstrated by Nomogram.ResultsAfter differential analysis, 33 genes were statistically significant (adjusted P < 0.05). Functional enrichment of these differential genes resulted in 85 Gene Ontology (GO) functions identified and 6 pathways enriched for the KEGG pathway. PPI networks and molecular complex assays identified 10 hub genes (adjusted P < 0.05). Random forest identified SMOC2 and SFRP4 as the most important, followed by FCER1G and FRZB. NeuraHF models (SMOC2, SFRP4, FCER1G and FRZB) were selected by artificial neural network model and had better diagnostic efficacy for the onset of DCM, compared with the traditional KG-DCM models (MYH7, ACTC1, TTN and LMNA). Finally, SFRP4 and FRZB were expressed higher in DCM verified by RT-PCR and as a factor for DCM identified by Nomogram.ConclusionsWe performed an integrated analysis and identified SFRP4 and FRZB as a new factor for DCM. But the exact mechanism still needs further experimental verification.

Brain-Region-Specific Differences in Protein Citrullination/Deimination in a Pre-Motor Parkinson's Disease Rat Model.

The detection of early molecular mechanisms and potential biomarkers in Parkinson's disease (PD) remains a challenge. Recent research has pointed to novel roles for post-translational citrullination/deimination caused by peptidylarginine deiminases (PADs), a family of calcium-activated enzymes, in the early stages of the disease. The current study assessed brain-region-specific citrullinated protein targets and their associated protein-protein interaction networks alongside PAD isozymes in the 6-hydroxydopamine (6-OHDA) induced rat model of pre-motor PD. Six brain regions (cortex, hippocampus, striatum, midbrain, cerebellum and olfactory bulb) were compared between controls/shams and the pre-motor PD model. For all brain regions, there was a significant difference in citrullinated protein IDs between the PD model and the controls. Citrullinated protein hits were most abundant in cortex and hippocampus, followed by cerebellum, midbrain, olfactory bulb and striatum. Citrullinome-associated pathway enrichment analysis showed correspondingly considerable differences between the six brain regions; some were overlapping for controls and PD, some were identified for the PD model only, and some were identified in control brains only. The KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways identified in PD brains only were associated with neurological, metabolic, immune and hormonal functions and included the following: "Axon guidance"; "Spinocerebellar ataxia"; "Hippo signalling pathway"; "NOD-like receptor signalling pathway"; "Phosphatidylinositol signalling system"; "Rap1 signalling pathway"; "Platelet activation"; "Yersinia infection"; "Fc gamma R-mediated phagocytosis"; "Human cytomegalovirus infection"; "Inositol phosphate metabolism"; "Thyroid hormone signalling pathway"; "Progesterone-mediated oocyte maturation"; "Oocyte meiosis"; and "Choline metabolism in cancer". Some brain-region-specific differences were furthermore observed for the five PAD isozymes (PADs 1, 2, 3, 4 and 6), with most changes in PAD 2, 3 and 4 when comparing control and PD brain regions. Our findings indicate that PAD-mediated protein citrullination plays roles in metabolic, immune, cell signalling and neurodegenerative disease-related pathways across brain regions in early pre-motor stages of PD, highlighting PADs as targets for future therapeutic avenues.

Single-Base Methylome Analysis of Sweet Cherry (Prunus avium L.) on Dwarfing Rootstocks Reveals Epigenomic Differences Associated with Scion Dwarfing Conferred by Grafting

Plant grafting using dwarfing rootstocks is one of the important cultivation measures in the sweet cherry (Prunus avium) industry. In this work, we aimed to explore the effects of the dwarfing rootstock “Pd1” (Prunus tomentosa) on sweet cherry ‘Shuguang2’ scions by performing morphological observations using the paraffin slice technique, detecting GA (gibberellin) and IAA (auxin) contents using UPLC-QTRAP-MS (ultra-performance liquid chromatography coupled with a hybrid triple quadrupole-linear ion trap mass spectrometer), and implementing integration analyses of the epigenome and transcriptome using whole-genome bisulfite sequencing and transcriptome sequencing. Anatomical analysis indicated that the cell division ability of the SAM (shoot apical meristem) in dwarfing plants was reduced. Pd1 rootstock significantly decreased the levels of GAs and IAA in sweet cherry scions. Methylome analysis showed that the sweet cherry genome presented 15.2~18.6%, 59.88~61.55%, 28.09~33.78%, and 2.99~5.28% methylation at total C, CG, CHG, and CHH sites, respectively. Shoot tips from dwarfing plants exhibited a hypermethylated pattern mostly due to increased CHH methylation, while leaves exhibited a hypomethylated pattern. According to GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis, DMGs (differentially methylated genes) and DEGs (differentially expressed genes) were enriched in hormone-related GO terms and KEGG pathways. Global correlation analysis between methylation and transcription revealed that mCpG in the gene body region enhanced gene expression and mCHH in the region near the TSS (transcription start site) was positively correlated with gene expression. Next, we found some hormone-related genes and TFs with significant changes in methylation and transcription, including SAURs, ARF, GA2ox, ABS1, bZIP, MYB, and NAC. This study presents a methylome map of the sweet cherry genome, revealed widespread DNA methylation alterations in scions caused by dwarfing rootstock, and obtained abundant genes with methylation and transcription alterations that are potentially involved in rootstock-induced growth changes in sweet cherry scions. Our findings can lay a good basis for further epigenetic studies on sweet cherry dwarfing and provide valuable new insight into understanding rootstock–scion interactions.

Transcriptome Analysis of Porphyromonas gingivalis Lipopolysaccharide-Induced Early Gene Expression in Human Gingival Keratinocytes.

Porphyromonas gingivalis lipopolysaccharide (PgLPS) is a significant virulence factor and a driver of early innate immune responses in epithelial cells. The presence of PgLPS in immediate proximity to gingival epithelium induces significant inflammatory responses. In primary human gingival keratinocytes (HGK), we utilized transcriptome analysis to elucidate the change in early gene expression induced by PgLPS. HGK cell cultures were treated with PgLPS (4 h), and RNA was extracted and prepared for RNA sequence (RNAseq) analysis. Differentially expressed genes (DEGs) were identified, and potential interactions between these genes were subsequently examined using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analytic approaches to identify significantly enriched pathways. Expression of genes associated with relevant pathways was evaluated using real-time quantitative reverse-transcription polymerase chain reaction (RT-qPCR). RNAseq analysis identified 25 DEGs, and GO and KEGG analytic approaches showed related genes expressed in two general pathways. First, pathways broadly related to urokinase and coagulation included the genes PLAU, PLAUR, and SerpinB2. In RT-qPCR analysis, these genes were induced by PgLPS over time (4-24 h), and these data were consistent with PgLPS induction of cell migration. Second, interleukin-1 (IL-1) receptor binding and cytokine-activity pathways were also enriched. Genes associated with these pathways included IL36G, IL1B, IL1RN, and CXCL14. RT-qPCR analysis confirmed PgLPS induction of genes associated with the IL-1family. When expression of IL1B and IL36G genes was examined in relation to their respective antagonists, only IL36G gene expression was increased. CXCL14 gene expression was reduced over time, and this was consistent with RNAseq analysis. Genes associated with significantly enriched GO and KEGG pathways are relevant to aspects of periodontal disease (PDD) pathogenesis. First, PgLPS induced expression of PLAU, PLAUR, and SerpinB2, and these changes were consistent with an increase in cell migration that was found. Second, both IL36G and IL1B gene expression was significantly induced, but only IL36G in relation to its selective antagonist (IL36RN) was increased. These data support that early upregulation of IL36G may serve as an alarmin that can drive early innate immune inflammatory responses in HGK. Further invivo testing of these findings is ongoing.

Unraveling potential gene biomarkers for dengue infection through RNA sequencing.

Dengue virus hijacks host cell mechanisms and immune responses in order to replicate efficiently. The interaction between the host and the virus affects the host's gene expression, which remains largely unexplored. This pilot study aimed to profile the host transcriptome as a potential strategy for identifying specific biomarkers for dengue prediction and detection. High-throughput RNA sequencing (RNA-seq) was employed to generate host transcriptome profiles in 16 dengue patients and 10 healthy controls. Differentially expressed genes (DEGs) were identified in patients with severe dengue and those with dengue with warning signs compared to healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to elucidate the functions of upregulated and downregulated genes. Compared to healthy controls, 6466 genes were significantly differentially expressed (p < 0.05) in the dengue with warning signs group and 3082 genes in the severe dengue group, with over half being upregulated. The major KEGG pathways implicated included transport and catabolism (14.4%-16.3%), signal transduction (6.6%-7.3%), global and overview maps (6.7%-7.1%), viral diseases (4.6%-4.8%), and the immune system (4.4%-4.6%). Several genes exhibited consistent and significant upregulation across all dengue patients, regardless of severity: Interferon alpha inducible protein 27 (IFI27), Potassium Channel Tetramerization Domain Containing 14 (KCTD14), Syndecan 1 (SDC1), DCC netrin 1 receptor (DCC), Ubiquitin C-terminal hydrolase L1 (UCHL1), Marginal zone B and B1 cell-specific protein (MZB1), Nestin (NES), C-C motif chemokine ligand 2 (CCL2), TNF receptor superfamily member 17 (TNFSF17), and TNF receptor superfamily member 13B (TNFRSF13B). Further analysis revealed potential biomarkers for severe dengue prediction, including TNF superfamily member 15 (TNFSF15), Plasminogen Activator Inhibitor-2 (SERPINB2), motif chemokine ligand 7 (CCL7), aconitate decarboxylase 1 (ACOD1), Metallothionein 1G (MT1G), and Myosin Light Chain Kinase (MYLK2), which were expressed 3.5 times, 2.9 times, 2.3 times, 2.1 times, 1.7 times, and 1.4 times greater, respectively, than dengue patients exhibiting warning signs. The identification of these host biomarkers through RNA-sequencing holds promising implications and potential to augment existing dengue detection algorithms, contributing significantly to improved diagnostic and prognostic capabilities.

Construction and validation of a prognostic model of angiogenesis-related genes in multiple myeloma

BackgroundAngiogenesis is associated with tumour growth, infiltration, and metastasis. This study aimed to detect the mechanisms of angiogenesis-related genes (ARGs) in multiple myeloma (MM) and to construct a new prognostic model.MethodsMM research foundation (MMRF)-CoMMpass cohort, GSE47552, GSE57317, and ARGs were sourced from public databases. Differentially expressed genes (DEGs) in the tumour and control cohorts in GSE47552 were determined through differential expression analysis and were enriched with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Weighted gene coexpression network analysis (WGCNA) was applied to derive modules linked to the ARG scores and obtain module genes in GSE47552. Differentially expressed ARGs (DE-ARGs) were selected for subsequent analyses by overlapping DEGs and module genes. Furthermore, prognostic genes were selected using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Depending on the prognostic genes, a risk model was constructed, and risk scores were determined. Moreover, MM samples from MMRF-CoMMpass were sorted into high- and low-risk teams on account of the median risk score. Additionally, correlations among clinical characteristics, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), immune analysis, immunotherapy predictions and the mRNA‒miRNA‒lncRNA network were carried out.ResultsA total of 898 DEGs, 211 module genes, 24 DE-ARGs and three prognostic genes (AKAP12, C11orf80 and EMP1) were selected for this study. Enrichment analysis revealed that the DEGs were related to 86 GO terms, such as ‘cytoplasmic translation’, and 41 KEGG pathways, such as ‘small cell lung cancer’. A prognostic gene-based risk model was created in MMRF-CoMMpass and confirmed with the GSE57317 dataset. Moreover, a nomogram was established on the basis of independent prognostic factors that have proven to be good predictors. In addition, the immune cell infiltration results suggested that memory B cells were enriched in the high-risk group and that immature B cells were enriched in the low-risk group. Finally, the mRNA‒miRNA‒lncRNA network demonstrated that hsa-miR-508-5p was tightly associated with EMP1 and AKAP12. RT‒qPCR was used to validate the expression of the genes associated with prognosis.ConclusionA new prognostic model of MM associated with ARGs was created and validated, providing a new perspective for exploring the connection between ARGs and MM.

Exploring the mechanisms of Cornus officinalis in the treatment of non-alcoholic steatohepatitis using network pharmacology, molecular docking and molecular dynamics simulations

Non-alcoholic steatohepatitis (NASH) is a predominant metabolic liver disease, typically characterized by hepatic steatosis, oxidative stress, and inflammation. The traditional Chinese medicine Cornus officinalis possesses anti-inflammatory and hepatoprotective pharmacological properties and has shown ameliorative effects on NASH. however, its mechanism of action remains unclear. This study aims to elucidate the mechanisms by which C. officinalis ameliorates NASH. The active components of C. officinalis were analyzed using the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), and the corresponding targets were predicted. Subsequently, the DisGeNET, GeneCards, and GEO databases were employed to identify NASH-related targets. Venn diagrams were used to intersect the C. officinalis targets with the NASH targets. Protein–protein interaction (PPI) networks were constructed using the STRING database, and PPI network analysis was performed using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the Database for Annotation, Visualization, and Integrated Discovery (DAVID), followed by molecular docking validation. Cornus officinalis was found to contain 20 major active ingredients corresponding to 672 potential targets, 61 of which overlapped with NASH targets. PPI network, GO, and KEGG pathway analyses identified four targets with the highest correlation, and molecular docking results indicated that the active ingredients of C. officinalis exhibited strong binding affinities to NASH targets. The treatment of NASH with C. officinalis is characterized by multiple active ingredients and multiple targets, underscoring the major advantage of traditional Chinese medicine in treating NASH.

Exploring the protective effect and molecular mechanism of betulin in Alzheimer's disease based on network pharmacology, molecular docking and experimental validation.

Alzheimer's disease (AD) is a neurodegenerative disorder that impairs learning and memory, with high rates of mortality. Birch bark has been traditionally used in the treatment of various skin ailments. Betulin (BT) is a key compound of birch bark that exhibits diverse pharmacological benefits and therapeutic potential in AD. However, the therapeutic effects and molecular mechanisms of BT in AD remain unclear. The present study aimed to predict the potential therapeutic targets of BT in the treatment of AD, and to determine the specific underlying molecular mechanisms through network pharmacology analysis and experimental validation. PharmMapper was used to predict the target genes of BT, and four disease databases were searched to screen for AD targets. The intersection targets were identified using the jveen website. Drug‑disease target protein‑protein interaction networks and hub genes were obtained and visualized using the Search Tool for the Retrieval of Interacting Genes/Proteins database and Cytoscape. The Database for Annotation, Visualization and Integrated Discovery was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and AutoDock was used for molecular docking analysis of BT and hub genes. Subsequently, the network‑predicted mechanisms of BT in AD were verified in vitro. A total of 495 BT and 1,386 AD targets were identified, and 120 were identified as potential targets of BT in the treatment of AD. The results of the molecular docking analysis revealed a strong binding affinity between BT and the hub genes. In addition, enrichment analyses of GO and KEGG pathways indicated that the neuroprotective effects of BT mainly involved the 'PI3K‑Akt signaling pathway'. The results of in vitro experiments demonstrated that pretreatment with BT for 2 h may ameliorate formaldehyde (FA)‑induced cytotoxicity and morphological changes in HT22 cells, and decrease FA‑induced Tau hyperphosphorylation and reactive oxygen species levels. Furthermore, the PI3K/AKT signaling pathway was activated and the expression levels of downstream proteins, namely GSK3β, Bcl‑2 and Bax, were modified following pre‑treatment with BT. Overall, the results of network pharmacology and in vitro analyses revealed that BT may reduce FA‑induced AD‑like pathology by modulating the PI3K/AKT signaling pathway, highlighting it as a potential multi‑target drug for the treatment of AD.

The Role of Connexin26 and Connexin30 in the Mouse Cochlea of Noise-Induced Hearing Loss.

We aimed to explore the role of connexin26 (Cx26) and connexin30 (Cx30) in the cochlea in noise-induced permanent threshold shifts (PTS) and temporary threshold shift (TTS). Prospective, controlled. Laboratory. A mouse model of noise-induced PTS and TTS was constructed. Western blots were used to detect the expression of Cx26 and Cx30 in the cochlea. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to assess the potential biological pathways. Both the expression of Cx26 and Cx30 showed a trend of first rising and then falling in noise-induced PTS. The expression of Cx26 increased greatly in the 24 hours noise exposure (P < .05) and reached the highest level in the 4 hours after noise exposure (P < .05), then decreased gradually and returned to the control level on the seventh day after the noise exposure, when compared with the control group. The expression of Cx30 showed a similar trend in noise-induced PTS. However, both the expression of Cx26 and Cx30 showed a trend of first falling and then rising in noise induced TTS. The expression of Cx26/Cx30 reached its lowest level in the 4 hours after noise exposure (P < .05), and then increased to the control level on the second day after noise exposure (P > .05), compared with the control group. The first KEGG and GO pathway may be related with oxidative phosphorylation. Cx26 and Cx30 may have an effect in noise induced PTS and TTS. Future studies are needed to confirm the results.