A brief survey of tools for genomic regions enrichment analysis

Gegen Qinlian Decoction improves Alzheimer's disease through TLR4/NF-κB/NLRP3 pathway

OBJECTIVE

Alzheimer's disease (AD) is a neurodegenerative disease that leads to dementia, but effective treatments are lacking. This study aims to evaluate the therapeutic effects of Gegen Qinlian Decoction (GGQLD) on AD and investigate the underlying mechanisms.

METHODS

Using network pharmacology and bioinformatics, we identified 376 active ingredients of GGQLD and 427 drug targets. Among these, 7 potential targets (CASP1, MKI67, NFKB1, TLR4, NLRP3, IL1B, and AKT1) were identified as intersecting targets of both GGQLD and AD. Functional enrichment analysis revealed that GGQLD regulates pyroptosis-related pathways. In vivo, GGQLD was administered to AD rat models to assess its effects on spatial learning, memory, and brain tissue injury.

RESULTS

GGQLD significantly reduced latency time by 40 % and increased platform crossings by 60 % in AD rats, demonstrating improved spatial learning and memory abilities. It also reduced hippocampal tissue damage and abnormal Aβ deposition. Mechanistically, GGQLD downregulated pyroptosis-related targets (TLR4, NF-κB, NLRP3, IL-1β, and Caspase-1), which were significantly upregulated in AD. ROC analysis demonstrated strong diagnostic significance for these genes, with AUC values exceeding 0.70. Functional enrichment and KEGG analysis further indicated that GGQLD exerts its therapeutic effects through multiple pathways, particularly the NOD-like receptor pathway, Necroptosis, and NF-kappa B pathway.

CONCLUSIONS

This study demonstrates that GGQLD improves spatial learning, reduces brain tissue damage, and alleviates inflammation in AD through the regulation of pyroptosis-related pathways, providing evidence for its potential as a therapeutic agent for AD.

Single cell RNA-sequencing identified CCR7+/RELB+/IRF1+ T cell responding for juvenile idiopathic arthritis pathogenesis

Background

To further explore the disease heterogeneity of different subtypes of Juvenile idiopathic arthritis (JIA) and analyze their pathogenesis mechanisms.

Method

The single-cell RNA sequencing (scRNA-seq) analysis of peripheral blood mononuclear cells (PBMCs) was carried out to investigate the disease heterogeneity and molecular mechanisms of immune responses in immune cells in JIA.

Result

In our study, we provided a immunological landscape of HLA-B27-positive JIA and HLA-B27-negative JIA immune cells at single cell RNA-Seq resolution. We found a higher proportion of CCR7+/RELB+/IRF1+ triple positive T cells in the peripheral blood of patients with JIA, and such T cells were predominantly present in HLA-B27+ JIA patients. Furthermore, we hypothesized that CCR7+/RELB+/IRF1+ triple positive T cells were highly activated T cells capable of promoting the differentiation of osteoclasts by producing IL-17, thus causing damage to cartilage in HLA-B27+ JIA patients. Unlike JIA patients, CCR7+/RELB+/IRF1+ triple positive T cells were not found in the peripheral blood of pSS patients and SLE patients, moreover, T cells from pSS patients and SLE patients were less able to produce IL-17 than those from JIA patients.

Conclusion

Our study provided evidence of cellular and molecular levels of involvement in JIA pathogenesis and identified the critical roles for T cells in JIA pathogenesis. Furthermore, our results suggested that there were significant differences in T cell composition and gene expression between HLA-B27+ JIA patients and HLA-B27- JIA patients. Our findings indicated that CCR7+/RELB+/IRF1+ positive T cells could damage the cartilage of HLA-B27+ JIA by producing cytokines such as IL-17.

Protein interactions, network pharmacology, and machine learning work together to predict genes linked to mitochondrial dysfunction in hypertrophic cardiomyopathy

This study looked at possible targets for hypertrophic cardiomyopathy (HCM), a condition marked by thickening of the ventricular wall, primarily in the left ventricle. We employed differential gene analysis and weighted gene co-expression network analysis (WGCNA) on samples. We then carried out an enrichment analysis. We also investigated the process of immunological infiltration. We employed six machine learning techniques and two protein-protein interaction (PPI) network gene selection approaches to search for the most characteristic gene (MCG). In the validation ladder, we verified the expression of MCG. Furthermore, we examined the MCG expression levels in HCM animal and cell models. Finally, we performed molecular docking and predicted potential medications for HCM treatment. 7975 differentially expressed genes (DEGs) were found in our study. We also identified 236 genes in the blue module using WGCNA. Screening at the transcriptome and protein levels was used to mine MCG. The final result screened CCAAT/Enhancer Binding Protein Delta (CEBPD) as MCG. We confirmed that MCG expression matched the outcomes of the experimental ladder. The level of CEBPD mRNA and protein was lowered in HCM animal and cellular models. Given that Abt-751 had the highest binding affinity to CEBPD, it might be a projected targeted medication. We found a new target gene for HCM called CEBPD, which is probably going to function by mitochondrial dysfunction. An innovative aim for the management or avoidance of HCM is offered by this analysis. Abt-751 may be a predicted targeted drug for HCM that had the greatest binding affinity with CEBPD.

Curcumin Analog J7 Attenuates Liver Fibrosis and Metabolic Dysregulation in a Rat Model of Type 2 Diabetes via Modulation of TGF-β/Smad and NF-κB/BCL-2/BAX Pathways

Objective

To evaluate the therapeutic potential of the curcumin analog J7 in protecting the liver and regulating glucose and lipid metabolism in rats with type 2 diabetes.

Methods

Bioinformatics methods were used to identify signaling pathways linked to diabetic liver disease. Diabetic rats were treated with curcumin, low-dose J7, or high-dose J7, and liver function and fibrosis were assessed through biochemical analyses, histopathology, immunohistochemistry, and ELISA.

Results

J7 administration significantly improved lisver function, reduced fibrosis, and regulated metabolic profiles in diabetic rats. J7 downregulated TGF-β1, NF-κB p65, and BAX, while upregulating BCL-2, showing superior effects to traditional curcumin in reducing TGF-β1 and inhibiting α-SMA expression.

Conclusion

J7 demonstrates potential as a therapeutic agent for managing liver complications in type 2 diabetes, effectively attenuating liver fibrosis and regulating metabolism through the modulation of key signaling pathways and proteins.

Clock protein LHY targets SNAT1 and negatively regulates the biosynthesis of melatonin in Hypericum perforatum

Hypericum perforatum, also known as "natural fluoxetine," is a commonly used herbal remedy for treating depression. It is unclear whether melatonin in plants regulated by the endogenous circadian clock system is like in vertebrates. In this work, we found that the melatonin signal and melatonin biosynthesis gene, serotonin N-acetyltransferase HpSNAT1, oscillates in a 24-hour cycle in H. perforatum. First, we constructed a yeast complementary DNA library of H. perforatum and found a clock protein HpLHY that can directly bind to the HpSNAT1 promoter. Second, it was confirmed that HpLHY inhibits the expression of HpSNAT1 by targeting the Evening Element. Last, it indicated that HpLHY-overexpressing plants had reduced levels of melatonin in 12-hour light/12-hour dark cycle photoperiod, while loss-of-function mutants exhibited high levels, but this rhythm seems to disappear as well. The results revealed the regulatory role of LHY in melatonin biosynthesis, which may make an important contribution to the field of melatonin synthesis regulation.

Integrative in silico approaches to analyse microRNA-mediated responses in human diseases

Advancements in sequencing technologies have facilitated omics level information generation for various diseases in human. High-throughput technologies have become a powerful tool to understand differential expression studies and transcriptional network analysis. An understanding of complex transcriptional networks in human diseases requires integration of datasets representing different RNA species including microRNA (miRNA) and messenger RNA (mRNA). This review emphasises on conceptual explanation of generalized workflow and methodologies to the miRNA mediated responses in human diseases by using different in silico analysis. Although, there have been many prior explorations in miRNA-mediated responses in human diseases, the advantages, limitations and overcoming the limitation through different statistical techniques have not yet been discussed. This review focuses on miRNAs as important gene regulators in human diseases, methodologies for miRNA-target gene prediction and data driven methods for enrichment and network analysis for miRnome-targetome interactions. Additionally, it proposes an integrative workflow to analyse structural components of networks obtained from high-throughput data. This review explains how to apply the existing methods to analyse miRNA-mediated responses in human diseases. It addresses unique characteristics of different analysis, its limitations and its statistical solutions influencing the choice of methods for the analysis through a workflow. Moreover, it provides an overview of promising common integrative approaches to comprehend miRNA-mediated gene regulatory events in biological processes in humans. The proposed methodologies and workflow shall help in the analysis of multi-source data to identify molecular signatures of various human diseases.

Systematic Analysis of the Relationship Between Elevated Zinc and Epilepsy

Previous studies have indicated a potential relationship between zinc and epilepsy. The aim of this study is to investigate the causal relationship between zinc, zinc-dependent carbonic anhydrase, and gray matter volume in brain regions enriched with zinc and epilepsy, as well as explore the possible mechanisms by which zinc contributes to epilepsy. First, this study assessed the risk causality between zinc, carbonic anhydrase, and gray matter volume alterations in zinc-enriched brain regions and various subtypes of epilepsy based on Two-sample Mendelian randomization analysis. And then, this study conducted GO/KEGG analysis based on colocalization analysis, MAGMA analysis, lasso regression, random forest model, and XGBoost model. The results of Mendelian randomization analyses showed a causal relationship between zinc, carbonic anhydrase-4, and generalized epilepsy (p = 0.044 , p = 0.010). Additionally, carbonic anhydrase-1 and gray matter volume of the caudate nucleus were found to be associated with epilepsy and focal epilepsy (p = 0.014, p = 0.003 and p = 0.022, p = 0.009). A colocalization relationship was found between epilepsy and focal epilepsy (PP.H4.abf = 97.7e - 2). Meanwhile, the MAGMA analysis indicated that SNPs associated with epilepsy and focal epilepsy were functionally localized to zinc-finger-protein-related genes (p < 1.0e - 5). The genes associated with focal epilepsy were found to have a molecular function of zinc ion binding (FDR = 2.3e - 6). After the onset of epilepsy, the function of the gene whose expression changed in the rats with focal epilepsy was enriched in the biological process of vascular response (FDR = 4.0e - 5). These results revealed mechanism of the increased risk of epilepsy caused by elevated zinc may be related to the increase of zinc ion-dependent carbonic anhydrase or the increase of the volume of zinc-rich caudate gray matter.

Rel Family Transcription Factor NFAT5 Upregulates COX2 via HIF-1α Activity in Ishikawa and HEC1a Cells

Nuclear factor of activated T cells 5 (NFAT5) and cyclooxygenase 2 (COX2; PTGS2) both participate in diverse pathologies including cancer progression. However, the biological role of the NFAT5-COX2 signaling pathway in human endometrial cancer has remained elusive. The present study explored whether NFAT5 is expressed in endometrial tumors and if NFAT5 participates in cancer progression. To gain insights into the underlying mechanisms, NFAT5 protein abundance in endometrial cancer tissue was visualized by immunohistochemistry and endometrial cancer cells (Ishikawa and HEC1a) were transfected with NFAT5 or with an empty plasmid. As a result, NFAT5 expression is more abundant in high-grade than in low-grade endometrial cancer tissue. RNA sequencing analysis of NFAT5 overexpression in Ishikawa cells upregulated 37 genes and downregulated 20 genes. Genes affected included cyclooxygenase 2 and hypoxia inducible factor 1α (HIF1A). NFAT5 transfection and/or treatment with HIF-1α stabilizer exerted a strong stimulating effect on HIF-1α promoter activity as well as COX2 expression level and prostaglandin E2 receptor (PGE2) levels. Our findings suggest that activation of NFAT5-HIF-1α-COX2 axis could promote endometrial cancer progression.

WASF3 overexpression affects the expression of circular RNA hsa-circ-0100153, which promotes breast cancer progression by sponging hsa-miR-31, hsa-miR-767-3p, and hsa-miR-935

Background

The WASF3 gene has been linked to promoting metastasis in breast cancer (BC) cells, and low expression reduces invasion potential. Circular RNAs (circRNAs) function as microRNA (miRNA) modulators and are involved in cancer progression, but the relationship between these factors remains unclear.

Methods

This study used bioinformatics methods and a computational approach to investigate the role of circRNAs and miRNAs in the context of WASF3 overexpression. Differentially expressed mRNAs, circRNAs, and miRNAs were identified using Gene Expression Omnibus (GEO) datasets. A competing endogenous RNA (ceRNA) network was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs. Functional and pathway enrichment analyses were predicted using a circRNA-miRNA-mRNA network.

Results

RNA expression patterns were significantly different between normal and tumor samples. A total of 190 circRNAs, 76 miRNAs, and 678 mRNAs were differentially expressed. The analysis of the circRNA-miRNA-mRNA regulatory network revealed interactions between hsa-circ-0100153, hsa-miR-31, hsa-miR-767-3p, and hsa-miR-935 with WASF3 in cancer. These interactions primarily function in DNA replication and the cell cycle.

Conclusions

This study reveals a mechanism by which WASF3 overexpression affects the expression of circRNAs hsa-circ-0100153, promoting BC progression by sponging hsa-miR-31/hsa-miR-767-3p /hsa-miR-935. This mechanism may increase the invasive potential of cancers, in addition to other reported molecular mechanisms involving the WASF3 gene.

Flame (v2.0): advanced integration and interpretation of functional enrichment results from multiple sources

Functional enrichment is the process of identifying implicated functional terms from a given input list of genes or proteins. In this article, we present Flame (v2.0), a web tool which offers a combinatorial approach through merging and visualizing results from widely used functional enrichment applications while also allowing various flexible input options. In this version, Flame utilizes the aGOtool, g: Profiler, WebGestalt, and Enrichr pipelines and presents their outputs separately or in combination following a visual analytics approach. For intuitive representations and easier interpretation, it uses interactive plots such as parameterizable networks, heatmaps, barcharts, and scatter plots. Users can also: (i) handle multiple protein/gene lists and analyse union and intersection sets simultaneously through interactive UpSet plots, (ii) automatically extract genes and proteins from free text through text-mining and Named Entity Recognition (NER) techniques, (iii) upload single nucleotide polymorphisms (SNPs) and extract their relative genes, or (iv) analyse multiple lists of differentially expressed proteins/genes after selecting them interactively from a parameterizable volcano plot. Compared to the previous version of 197 supported organisms, Flame (v2.0) currently allows enrichment for 14 436 organisms.

AVAILABILITY AND IMPLEMENTATION

Web Application: http://flame.pavlopouloslab.info. Code: https://github.com/PavlopoulosLab/Flame. Docker: https://hub.docker.com/r/pavlopouloslab/flame.

Ten quick tips for avoiding pitfalls in multi-omics data integration analyses

Data are the most important elements of bioinformatics: Computational analysis of bioinformatics data, in fact, can help researchers infer new knowledge about biology, chemistry, biophysics, and sometimes even medicine, influencing treatments and therapies for patients. Bioinformatics and high-throughput biological data coming from different sources can even be more helpful, because each of these different data chunks can provide alternative, complementary information about a specific biological phenomenon, similar to multiple photos of the same subject taken from different angles. In this context, the integration of bioinformatics and high-throughput biological data gets a pivotal role in running a successful bioinformatics study. In the last decades, data originating from proteomics, metabolomics, metagenomics, phenomics, transcriptomics, and epigenomics have been labelled -omics data, as a unique name to refer to them, and the integration of these omics data has gained importance in all biological areas. Even if this omics data integration is useful and relevant, due to its heterogeneity, it is not uncommon to make mistakes during the integration phases. We therefore decided to present these ten quick tips to perform an omics data integration correctly, avoiding common mistakes we experienced or noticed in published studies in the past. Even if we designed our ten guidelines for beginners, by using a simple language that (we hope) can be understood by anyone, we believe our ten recommendations should be taken into account by all the bioinformaticians performing omics data integration, including experts.