The microRNA-211-5p/P2RX7/ERK/GPX4 axis regulates epilepsy-associated neuronal ferroptosis and oxidative stress.

Ferroptosis is an iron-dependent cell death mechanism involving the accumulation of lipid peroxides. As a critical regulator, glutathione peroxidase 4 (GPX4) has been demonstrated to be downregulated in epilepsy. However, the mechanism of ferroptosis in epilepsy remains unclear. In this study, bioinformatics analysis, analysis of epilepsy patient blood samples and cell and mouse experiments revealed strong associations among epilepsy, ferroptosis, microRNA-211-5p and purinergic receptor P2X 7 (P2RX7). P2RX7 is a nonselective ligand-gated homotrimeric cation channel, and its activation mainly increases neuronal activity during epileptic seizures. In our study, the upregulation of P2RX7 in epilepsy was attributed to the downregulation of microRNA (miR)-211-5p. Furthermore, P2RX7 has been found to regulate GPX4/HO-1 by alleviating lipid peroxidation induced by suppression of the MAPK/ERK signaling pathway in murine models. The dynamic decrease in miR-211-5p expression induces hypersynchronization and both nonconvulsive and convulsive seizures, and forebrain miR-211-5p suppression exacerbates long-lasting pentylenetetrazole-induced seizures. Additionally, in this study, induction of miR-211-5p expression or genetic-silencing of P2RX7 significantly reduced the seizure score and duration in murine models through the abovementioned pathways. These results suggest that the miR-211-5p/P2RX7 axis is a novel target for suppressing both ferroptosis and epilepsy.

Combining single-cell RNA sequencing data and transcriptomic data to unravel potential mechanisms and signature genes of the progression of idiopathic pulmonary fibrosis to lung adenocarcinoma and predict therapeutic agents.

Patients with idiopathic pulmonary fibrosis (IPF) have a significantly higher prevalence of lung adenocarcinoma (LUAD) than normal subjects, although the underlying association is unclear. The raw data involved were obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis were used to screen for differentially expressed genes (DEGs) and modular signature genes (MSGs). Genes intersecting DEGs and MSGs were considered hub genes for IPF and LUAD. Machine learning algorithms were applied to capture epithelial cell-derived signature genes (EDSGs) shared. External cohort data were exploited to validate the robustness of EDSGs. Immunohistochemical staining and K-M plots were used to denote the prognostic value of EDSGs in LUAD. Based on EDSGs, we constructed a TF-gene-miRNA regulatory network. Molecular docking can validate the strength of action between candidate drugs and EDSGs. Epithelial cells, 650 DEGs, and 1773 MSGs were shared by IPF and LUAD. As for 379 hub genes, we performed pathway and functional enrichment analysis. By analyzing sc-RNA seq data, we identified 1234 marker genes of IPF epithelial cell-derived and 1481 of LUAD. And these genes shared 8 items with 379 hub genes. Through the machine learning algorithms, we further fished TRIM2, S100A14, CYP4B1, LMO7, and SFN. The ROC curves emphasized the significance of EDSGs in predicting the onset of LUAD and IPF. The TF-gene-miRNA network revealed regulatory relationships behind EDSGs. Finally, we predicted appropriate therapeutic agents. Our study preliminarily identified potential mechanisms between IPF and LUAD, which will inform subsequent studies.

Comprehensive analyses of bioinformatics applications in the fight against COVID-19 pandemic.

Novel coronavirus disease 2019 (COVID-19) is a global pandemic caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), which can be transmitted from person to person. As of September 21, 2021, over 228 million cases were diagnosed as COVID-19 infection in more than 200 countries and regions worldwide. The death toll is more than 4.69 million and the mortality rate has reached about 2.05% as it has gradually become a global plague, and the numbers are growing. Therefore, it is important to gain a deeper understanding of the genome and protein characteristics, clinical diagnostics, pathogenic mechanisms, and the development of antiviral drugs and vaccines against the novel coronavirus to deal with the COVID-19 pandemic. The traditional biology technologies are limited for COVID-19-related studies to understand the pandemic happening. Bioinformatics is the application of computational methods and analytical tools in the field of biological research which has obvious advantages in predicting the structure, product, function, and evolution of unknown genes and proteins, and in screening drugs and vaccines from a large amount of sequence information. Here, we comprehensively summarized several of the most important methods and applications relating to COVID-19 based on currently available reports of bioinformatics technologies, focusing on future research for overcoming the virus pandemic. Based on the next-generation sequencing (NGS) and third-generation sequencing (TGS) technology, not only virus can be detected, but also high quality SARS-CoV-2 genome could be obtained quickly. The emergence of data of genome sequences, variants, haplotypes of SARS-CoV-2 help us to understand genome and protein structure, variant calling, mutation, and other biological characteristics. After sequencing alignment and phylogenetic analysis, the bat may be the natural host of the novel coronavirus. Single-cell RNA sequencing provide abundant resource for discovering the mechanism of immune response induced by COVID-19. As an entry receptor, angiotensin-converting enzyme 2 (ACE2) can be used as a potential drug target to treat COVID-19. Molecular dynamics simulation, molecular docking and artificial intelligence (AI) technology of bioinformatics methods based on drug databases for SARS-CoV-2 can accelerate the development of drugs. Meanwhile, computational approaches are helpful to identify suitable vaccines to prevent COVID-19 infection through reverse vaccinology, Immunoinformatics and structural vaccinology.

A Multi-Epitope Fusion Protein-Based p-ELISA Method for Diagnosing Bovine and Goat Brucellosis.

In recent years, the incidence of brucellosis has increased annually, causing tremendous economic losses to animal husbandry in a lot of countries. Therefore, developing rapid, sensitive, and specific diagnostic techniques is critical to control the spread of brucellosis. In this study, bioinformatics technology was used to predict the B cell epitopes of the main outer membrane proteins of Brucella, and the diagnostic efficacy of each epitope was verified by an indirect enzyme-linked immunosorbent assay (iELISA). Then, a fusion protein containing 22 verified epitopes was prokaryotically expressed and used as an antigen in paper-based ELISA (p-ELISA) for serodiagnosis of brucellosis. The multi-epitope-based p-ELISA was evaluated using a collection of brucellosis-positive and -negative sera collected from bovine and goat, respectively. Receiver operating characteristic (ROC) curve analysis showed that the sensitivity and specificity of detection-ELISA in diagnosing goat brucellosis were 98.85 and 98.51%. The positive and the negative predictive values were 99.29 and 98.15%, respectively. In diagnosing bovine brucellosis, the sensitivity and specificity of this method were 97.85 and 96.61%, with the positive and negative predictive values being identified as 98.28 and 97.33%, respectively. This study demonstrated that the B cell epitopes contained in major antigenic proteins of Brucella can be a very useful antigen source in developing a highly sensitive and specific method for serodiagnosis of brucellosis.

Screening and Identification of Differentially Expressed Genes Between Diabetic Nephropathy Glomerular and Normal Glomerular via Bioinformatics Technology.

BACKGROUND: Diabetes is a chronic metabolic disease characterized by disorders of glucose and lipid metabolism. Its most serious microvascular complication is diabetic nephropathy (DN), which is characterized by varying degrees of proteinuria and progressive glomerulosclerosis, eventually progressing to end-stage renal failure. OBJECTIVE: The aim of this research is to identify hub genes that might serve as genetic markers to enhance the diagnosis, treatment, and prognosis of DN. METHODS: The procedures of the study include access to public data, identification of differentially expressed genes (DEGs) by GEO2R, and functional annotation of DEGs using enrichment analysis. Subsequently, the construction of the protein-protein interaction (PPI) network and identification of significant modules were performed. Finally, the hub genes were identified and analyzed, including clustering analysis, Pearson's correlation coefficient analysis, and multivariable linear regression analysis. RESULTS: Between the GSE30122 and GSE1009 datasets, a total of 142 DEGs were identified, which were mainly enriched in cell migration, platelet activation, glomerulus development, glomerular basement membrane development, focal adhesion, regulation of actin cytoskeleton, and the PI3K-AKT signaling pathway. The PPI network was composed of 205 edges and 142 nodes. A total of 10 hub genes (VEGFA, NPHS1, WT1, PODXL, TJP1, FYN, SULF1, ITGA3, COL4A3, and FGF1) were identified from the PPI network. CONCLUSION: The DEGs between DN and control glomeruli samples may be involved in the occurrence and development of DN. It was speculated that hub genes might be important inhibitory genes in the pathogenesis of diabetic nephropathy, therefore, they are expected to become the new gene targets for the treatment of DN.

Effects of neutrophil DNA methylation on periodontitis and research progress in bioinformatics / 国际生物医学工程杂志

Periodontitis is a chronic infectious disease leading to periodontal connective tissue destruction and alveolar bone resorption, which is widely prevalent and seriously endangers the oral and systemic health of a wide range of patients. The host immune inflammatory response plays a major role in the tissue destruction of periodontitis. Polymorphonuclear neutrophils (PMNs), as one of the important immune cell components in periodontal tissues, can trigger the host immune inflammatory response through the release of pro-inflammatory factors, which in turn leads to periodontitis. DNA methylation can influence the function of immune cells by regulating gene expression. Bioinformatics technology can provide new ideas for the treatment of periodontitis by analyzing the gene expression profiles and DNA methylation data of periodontal tissues from public databases of periodontitis patients and healthy populations, uncovering key DNA methylation genes of PMNs, and elucidating the influence of these genes on the pathological progression of periodontitis.

Medication rule and mechanism of traditional Chinese medicine in treating metabolism-associated fatty liver disease based on bioinformatics technology / 数字中医药（英文）

@#[Objective[ To analyze the main syndrome types, medication rules, and core prescription characteristics of traditional Chinese medicine (TCM) in the treatment of metabolism-associated fatty liver disease (MAFLD), and to predict the anti-MAFLD mechanism of core formula, so as to provide references for the clinical application of TCM and the development of new drugs. [Methods] Literature research on TCM in treating MAFLD was retrieved from China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), and Wanfang Database since the establishment of the database to July 2022. Excel 2019 and Chinese Medicine Inheritance Computing Platform (V3.0) were used for frequency analysis, association rule analysis, and cluster analysis of effective prescriptions. The key components, targets, and action pathways of anti-MAFLD core formulas were predicted by network pharmacology. Finally, the interactions between the obtained core components and their core targets were verified reversely by molecular docking technology. [Results] A total of 218 articles were screened and selected, including 352 prescriptions, involving 270 traditional Chinese herbs. The drugs were used a total of 3 901 times, and a total of 10 915 cases were collected, among which the prevalence rate was higher in males. The main types of TCM syndrome included intermingled phlegm and blood stasis syndrome, liver depression and spleen deficiency syndrome, and damp-heat in liver and gallbladder syndrome, among which Shanzha (Crataegi Fructus), Danshen (Salviae Miltiorrhizae Radix et Rhizoma), Fuling (Poria), Zexie (Alismatis Rhizoma), Chaihu (Bupleuri Radix), and Baizhu (Atractylodis Macrocephalae Rhizoma) were the most frequently used. The properties of Chinese medicine primarily encompassed thermal characteristics, with a predominant emphasis on cold and warm; the flavors of herbs were predominantly characterized by bitterness and sweetness, while the majority exhibited tropism towards the spleen and liver meridians. The drugs were primarily classified based on their efficacy in tonifying deficiencies, promoting diuresis and moistening, enhancing blood circulation and removing blood stasisheat-clearing, etc. The association rules were employed to derive a set of 20 core drug pairs, while cluster analysis was utilized to identify three distinct groups of core drug combinations. Network pharmacological showed that the main components of the core formula “Shanzha (Crataegi Fructus) - Danshen (Salviae Miltiorrhizae Radix et Rhizoma) - Zexie (Alismatis Rhizoma) - Chaihu (Bupleuri Radix) - Fuling (Poria)” in the treatment of MAFLD were quercetin, apigenin, puerarin, luteolin, ursolic acid, kaempferol, tanshinone IIA, emodin, paeonol, etc., which involved RAC-alpha serine/threonine-protein kinase 1 (AKT1), cellular tumor antigen p53 (TP53), interleukin (IL)-6, IL-1β, signal transducer and activator of transcription 3 (STAT3), epidermal growth factor receptor (EGFR), peroxisome proliferative activated receptor gamma (PPARG), and other key targets. The molecular docking results showed that the core components had good binding to lipid and atherosclerosis, and phosphatidylinositol 3 kinase (PI3K)/AKT signaling pathway-associated proteins. [Conclusion] The main principles of TCM for the treatment of MAFLD involve soothing the liver and strengthening the spleen, eliminating phlegm and dampness, clearing heat and dampness, as well as promoting blood circulation and removing blood stasis. The core formula may exert anti-MAFLD effects mediated through multiple components, targets, and signaling pathways. This study establishes a theoretical foundation for the clinical application of TCM in the treatment of MAFLD, and serves as a reference for further exploration of new drugs against MAFLD.

CysC specific peptides: bioinformatics analysis and mass spectrometry verification / 临床检验杂志

Objective To analyze the specific peptide of cystatin C (CysC) and its characteristics by bioinformatics technology,and verify the predicted results by mass spectrometry.Methods Online software was applied to analyze the physicochemical properties and homology of CysC peptides hydrolyzed by trypsin and predict the associated parameters of ionized fragmentation of specific peptide by mass spectrometry.Precursor ion scan and product ion scan were conducted on the samples of synthetic specific peptide.The recombinant human CysC and serum samples were analyzed by mass spectrometry after trypsin digestion.The results of analysis were compared with the outcomes predicted by bioinformatics.Results T3 (ALDFAVGEYNK) was considered as the specific peptide of CysC by software analysis.When selecting[M + 2H] 2 + for product ion scan,almost all the y and b ions of fragmentation were observed using tandem mass spectrometry (MS/MS),showing consistency with Skyline predictions.Moreover,both the peptides from the human recombinant CysC and serum sample following the trypsin digestion were eluted at the same time with the isotope-labeled T3 * under the fixed conditions.Conclusion Bioinformatics technology could be available for picking out the specific peptides of target protein quickly and efficiently and predicting the ionized fragmentation precisely by mass spectrometry scanning.