Neuroactive Ligand-receptor Interaction Research Articles

An integrative analysis of lipidomics and transcriptomics in various mouse brain regions in response to real-ambient PM2.5 exposure

Exposure to Fine particulate matter (PM2.5) has been associated with various neurological disorders. However, the underlying mechanisms of PM2.5-induced adverse effects on the brain are still not fully defined. Multi-omics analyses could offer novel insights into the mechanisms of PM2.5-induced brain dysfunction. In this study, a real-ambient PM2.5 exposure system was applied to male C57BL/6 mice for 16 weeks, and lipidomics and transcriptomics analysis were performed in four brain regions. The findings revealed that PM2.5 exposure led to 548, 283, 304, and 174 differentially expressed genes (DEGs), as well as 184, 89, 228, and 49 distinctive lipids in the hippocampus, striatum, cerebellum, and olfactory bulb, respectively. Additionally, in most brain regions, PM2.5-induced DEGs were mainly involved in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction, and calcium signaling pathway, while PM2.5-altered lipidomic profile were primarily enriched in retrograde endocannabinoid signaling and biosynthesis of unsaturated fatty acids. Importantly, mRNA-lipid correlation networks revealed that PM2.5-altered lipids and DEGs were obviously enriched in pathways involving in bile acid biosynthesis, De novo fatty acid biosynthesis, and saturated fatty acids beta-oxidation in brain regions. Furthermore, multi-omics analyses revealed that the hippocampus was the most sensitive part to PM2.5 exposure. Specifically, dysregulation of Pla2g1b, Pla2g, Alox12, Alox15, and Gpx4 induced by PM2.5 were closely correlated to the disruption of alpha-linolenic acid, arachidonic acid and linoleic acid metabolism in the hippocampus. In summary, our findings highlight differential lipidomic and transcriptional signatures of various brain regions by real-ambient PM2.5 exposure, which will advance our understanding of potential mechanisms of PM2.5-induecd neurotoxicity.

Shared genetics and causal relationships between major depressive disorder and COVID-19 related traits: a large-scale genome-wide cross-trait meta-analysis.

The comorbidity between major depressive disorder (MDD) and coronavirus disease of 2019 (COVID-19) related traits have long been identified in clinical settings, but their shared genetic foundation and causal relationships are unknown. Here, we investigated the genetic mechanisms behind COVID-19 related traits and MDD using the cross-trait meta-analysis, and evaluated the underlying causal relationships between MDD and 3 different COVID-19 outcomes (severe COVID-19, hospitalized COVID-19, and COVID-19 infection). In this study, we conducted a comprehensive analysis using the most up-to-date and publicly available GWAS summary statistics to explore shared genetic etiology and the causality between MDD and COVID-19 outcomes. We first used genome-wide cross-trait meta-analysis to identify the pleiotropic genomic SNPs and the genes shared by MDD and COVID-19 outcomes, and then explore the potential bidirectional causal relationships between MDD and COVID-19 outcomes by implementing a bidirectional MR study design. We further conducted functional annotations analyses to obtain biological insight for shared genes from the results of cross-trait meta-analysis. We have identified 71 SNPs located on 25 different genes are shared between MDD and COVID-19 outcomes. We have also found that genetic liability to MDD is a causal factor for COVID-19 outcomes. In particular, we found that MDD has causal effect on severe COVID-19 (OR = 1.832, 95% CI = 1.037-3.236) and hospitalized COVID-19 (OR = 1.412, 95% CI = 1.021-1.953). Functional analysis suggested that the shared genes are enriched in Cushing syndrome, neuroactive ligand-receptor interaction. Our findings provide convincing evidence on shared genetic etiology and causal relationships between MDD and COVID-19 outcomes, which is crucial to prevention, and therapeutic treatment of MDD and COVID-19.

Gene set enrichment analysis identifies immune subtypes of kidney renal clear cell carcinoma with significantly different molecular and clinical properties.

Kidney renal clear cell carcinoma (KIRC) is the most prevalent renal malignancy, marked by a high abundance of tumor-infiltrating lymphocytes (TILs) and an unfavorable prognosis upon metastasis. Numerous studies have demonstrated that KIRC possesses a tumor microenvironment that is highly heterogeneous, and this is associated with significant variations in the effectiveness of most first-line drugs administered to KIRC patients. Therefore, it is crucial to classify KIRC based on the tumor microenvironment, although these subtyping techniques are still inadequate. By applying gene set enrichment scores of 28 immune signatures, we conducted a hierarchical clustering of KIRC and determined its immune subtypes. In addition, we conducted a comprehensive exploration of the molecular and clinical features of these subtypes, including survival prognosis, proliferation, stemness, angiogenesis, tumor microenvironment, genome instability, intratumor heterogeneity, and pathway enrichment. Through cluster analysis, two immune subtypes of KIRC were identified and termed Immunity-High (Immunity-H) and Immunity-Low (Immunity-L). This clustering outcome was consistent in four independent KIRC cohorts. The subtype Immunity-H exhibited elevated levels of TILs, tumor aneuploidy, homologous recombination deficiency, stemness, and proliferation potential, along with a poorer prognosis for survival. Despite this, the Immunity-L subtype demonstrated elevated intratumor heterogeneity and a stronger angiogenesis signature in contrast to Immunity-H. According to the results of pathway enrichment analysis, the Immunity-H subtype was found to be highly enriched in immunological, oncogenic, and metabolic pathways, whereas the Immunity-L subtype was highly enriched in angiogenic, neuroactive ligand-receptor interaction, and PPAR pathways. Based on the enrichment of immune signatures in the tumor microenvironment, KIRC can be categorized into two immune subtypes. The two subtypes demonstrate considerably distinct molecular and clinical features. In KIRC, an increase in immune infiltration is linked to a poor prognosis. Patients with Immunity-H KIRC may exhibit active responses to PPAR and immune checkpoint inhibitors, whereas patients with Immunity-L may manifest favorable responses to anti-angiogenic agents and immune checkpoint inhibitors. The immunological classification provides molecular insights into KIRC immunity, as well as clinical implications for the management of this disease.

Revealing the Mechanisms of Byu dMar 25 in the Treatment of Alzheimer's Disease through Network Pharmacology, Molecular Docking, and In Vivo Experiment.

Alzheimer's disease (AD) is the most common neurodegenerative disease, severely reducing the cognitive level and life quality of patients. Byu dMar 25 (BM25) has been proved to have a therapeutic effect on AD. However, the pharmacological mechanism is still unclear. Therefore, this study aims to reveal the potential mechanism of BM25 affecting AD from the perspective of network pharmacology and experimental validation. The potential active ingredients of BM25 were obtained from the TCMSP database and literature. Possible targets were predicted using SwissTargetPrediction tools. AD-related genes were identified by using GeneCards, OMIM, DisGeNET, and Drugbank databases. The candidate genes were obtained by extraction of the intersection network. Additionally, the "drug-target-disease" network was constructed by Cytoscape 3.7.2 for visualization. The PPI network was constructed by the STRING database, and the core network modules were filtered by Cytoscape 3.7.2. Enrichment analysis of GO and KEGG was carried out in the Metascape platform. Ledock software was used to dock the critical components with the core target. Furthermore, protein levels were evaluated by immunohistochemistry. In this study, 112 active components, 1112 disease candidate genes, 3084 GO functions, and 277 KEGG pathways were obtained. Molecular docking showed that the effective components of BM25 in treating AD were β-asarone and hydroxysafflor yellow A. The most important targets were APP, PIK3R1, and PIK3CA. Enrichment analysis indicated that the Golgi genetic regulation, peroxidase activity regulation, phosphatidylinositol 3-kinase complex IA, 5-hydroxytryptamine receptor complexes, cancer pathways, and neuroactive ligand-receptor interactions played vital roles against AD. The rat experiment verified that BM25 affected PI3K-Akt pathway activation in AD. This study reveals the mechanism of BM25 in treating AD with network pharmacology, which provides a foundation for further study on the molecular mechanism of AD treatment.

Peptidomics analysis of human breast milk from women with postpartum depression reveals its potential pathogenesis.

Postpartum depression (PPD) is a prevalent psychiatric disorder during the postnatal period, and it exerts adverse impacts not only on mothers but also on infants, impairing the well-being of the whole family. However, the role of peptides in the breast milk of mothers with PPD has not been studied. The purpose of this study was to unveil the peptidomic profile of PPD from breast milk samples. We performed comparative peptidomic profiling of human breast milk from PPD and control mothers using liquid chromatography-tandem mass spectrometry technology with iTRAQ-8 labelling. GO and KEGG pathway analyses of precursor proteins were used to predict the underlying biological functions of differentially expressed peptides (DEPs). Ingenuity Pathway Analysis (IPA) was further performed to explore the interactions and involved pathways of DEPs. A total of 294 peptides from 62 precursor proteins were identified to be differentially expressed in the breast milk of PPD mothers compared with the control group. Bioinformatics analysis predicted that these DEPs were associated with ECM-receptor interaction, neuroactive ligand-receptor interaction, cell adhesion molecule binding and oxidative stress in macrophages. These results indicate that DEPs from human breast milk may play a part in PPD and become promising noninvasive biomarkers.

Intergenerational toxic effects of parental exposure to [Cn mim]NO3 (n = 2,4,6) on nervous and skeletal development in zebrafish offspring.

Ionic liquids (ILs) are thought to have negative effects on human health. Researchers have explored the effects of ILs on zebrafish development during the early stages, but the intergenerational toxicity of ILs on zebrafish development has rarely been reported. Herein, parental zebrafish were exposed to different concentrations (0, 12.5, 25, and 50 mg/L) of [Cn mim]NO3 (n = 2, 4, 6) for 1 week. Subsequently, the F1 offspring were cultured in clean water for 96 h. [Cn mim]NO3 (n = 2, 4, 6) exposure inhibited spermatogenesis and oogenesis in F0 adults, even causing obvious lacunae in the testis and atretic follicle oocytes in ovary. After parental exposure to [Cn mim]NO3 (n = 2, 4, 6), the body length and locomotor behavior were measured in F1 larvae at 96 hours post-fertilization (hpf). The results showed that the higher the concentration of [Cn mim]NO3 (n = 2, 4, 6), the shorter the body length and swimming distance, and the longer the immobility time. Besides, a longer alkyl chain length of [Cn mim]NO3 had a more negative effect on body length and locomotor behavior. RNA-seq analysis revealed several downregulated differentially expressed genes (DEGs)-grin1b, prss1, gria3a, and gria4a-enriched in neurodevelopment-related pathways, particularly the pathway for neuroactive ligand-receptor interaction. Moreover, several upregulated DEGs, namely col1a1a, col1a1b, and acta2, were mainly associated with skeletal development. Expression of DEGs was tested by RT-qPCR, and the outcomes were consistent with those obtained from RNA-Seq. We provide evidence showing the effects of parental exposure to ILs on the regulation of nervous and skeletal development in F1 offspring, demonstrating intergenerational effects.

Using a Quantitative High-Throughput Screening Platform to Identify Molecular Targets and Compounds as Repurposing Candidates for Endometriosis

Endometriosis, defined as the growth of hormonally responsive endometrial-like tissue outside of the uterine cavity, is an estrogen-dependent, chronic, pro-inflammatory disease that affects up to 11.4% of women of reproductive age and gender-diverse people with a uterus. At present, there is no long-term cure, and the identification of new therapies that provide a high level of efficacy and favourable long-term safety profiles with rapid clinical access are a priority. In this study, quantitative high-throughput compound screens of 3517 clinically approved compounds were performed on patient-derived immortalized human endometrial stromal cell lines. Following assay optimization and compound criteria selection, a high-throughput screening protocol was developed to enable the identification of compounds that interfered with estrogen-stimulated cell growth. From these screens, 23 novel compounds were identified, in addition to their molecular targets and in silico cell-signalling pathways, which included the neuroactive ligand–receptor interaction pathway, metabolic pathways, and cancer-associated pathways. This study demonstrates for the first time the feasibility of performing large compound screens for the identification of new translatable therapeutics and the improved characterization of endometriosis molecular pathophysiology. Further investigation of the molecular targets identified herein will help uncover new mechanisms involved in the establishment, symptomology, and progression of endometriosis.

Identification of key immune genes of osteoporosis based on bioinformatics and machine learning.

Immunity is involved in a variety of bone metabolic processes, especially osteoporosis. The aim of this study is to explore new bone immune-related markers by bioinformatics method and evaluate their ability to predict osteoporosis. The mRNA expression profiles were obtained from GSE7158 in Gene expression Omnibus (GEO), and immune-related genes were obtained from ImmPort database (https://www.immport.org/shared/). immune genes related to bone mineral density(BMD) were screened out for differential analysis. protein-protein interaction (PPIs) networks were used to analyze the interrelationships between different immune-related genes (DIRGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of DIRGs function were performed. A least absolute shrinkage and selection operation (LASSO) regression model and multiple Support Vector Machine-Recursive Feature Elimination (mSVM-RFE) model were constructed to identify the candidate genes for osteoporosis prediction The receiver operator characteristic (ROC) curves were used to validate the performances of predictive models and candidate genes in GEO database (GSE7158,GSE13850).Through the RT - qPCR verify the key genes differentially expressed in peripheral blood mononuclear cells Finally, we constructed a nomogram model for predicting osteoporosis based on five immune-related genes. CIBERSORT algorithm was used to calculate the relative proportion of 22 immune cells. A total of 1158 DEGs and 66 DIRGs were identified between high-BMD and low-BMD women. These DIRGs were mainly enriched in cytokine-mediated signaling pathway, positive regulation of response to external stimulus and the cellular components of genes are mostly localized to external side of plasma membrane. And the KEGG enrichment analysis were mainly involved in Cytokine-cytokine receptor interaction, PI3K-Akt signaling pathway, Neuroactive ligand-receptor interaction,Natural killer cell mediated cytotoxicity. Then five key genes (CCR5, IAPP, IFNA4, IGHV3-73 and PTGER1) were identified and used as features to construct a predictive prognostic model for osteoporosis using the GSE7158 dataset. Immunity plays an important role in the development of osteoporosis.CCR5, IAPP, IFNA4, IGHV3-73 and PTGER1were play an important role in the occurrences and diagnosis of OP.

Integrated fecal microbiota and metabolomics analysis of the orlistat intervention effect on polycystic ovary syndrome rats induced by letrozole combined with a high-fat diet

BackgroundThis study aimed to compare the characteristics of the gut microbiota and their metabolite profiles between polycystic ovary syndrome (PCOS) and orlistat-treated PCOS rats (ORL-PCOS), which could help to better understand the underlying mechanism of the effect of orlistat on PCOS.MethodsPCOS rat models were established using letrozole combined with a high-fat diet. Ten rats were randomly selected as a PCOS control group (PCOS). The other three groups (n = 10/group) were additionally supplemented with different doses of orlistat (low, medium, high). Then, fecal samples of the PCOS and ORL-PCOS groups were analysed by 16S rRNA gene sequencing and untargeted metabolomics. Blood samples were collected to detect serum sex hormones and lipids.ResultsThe results showed that orlistat attenuated the body weight gain, decreased the levels of T, LH, the LH/FSH ratio, TC, TG and LDL-C; increased the level of E2; and improved estrous cycle disorder in PCOS rats. The bacterial richness and diversity of the gut microbiota in the ORL-PCOS group were higher than those in the PCOS group. The ratio of Firmicutes to Bacteroidetes was decreased with orlistat treatment. Moreover, orlistat treatment led to a significant decrease in the relative abundance of Ruminococcaceae and Lactobacillaceae, and increases in the abundances of Muribaculaceae and Bacteroidaceae. Metabolic analysis identified 216 differential fecal metabolites in total and 6 enriched KEGG pathways between the two groups, including steroid hormone biosynthesis, neuroactive ligand-receptor interaction and vitamin digestion and absorption. Steroid hormone biosynthesis was the pathway with the most significant enrichment. The correlations between the gut microbiota and differential metabolites were calculated, which may provide a basis for understanding the composition and function of microbial communities.ConclusionsOur data suggested that orlistat exerts a PCOS treatment effect, which may be mediated by modifying the structure and composition of the gut microbiota, as well as the metabolite profiles of PCOS rats.

Network pharmacology-based prediction of efficacy and mechanism of Chongmyunggongjin-dan acting on Alzheimer’s disease

Objectives: Network pharmacology is a method of constructing and analyzing a drug-compound-target network to predict potential efficacy and mechanisms related to drug targets. In that large-scale analysis can be performed in a short time, it is considered a suitable tool to explore the function and role of herbal medicine. Thus, we investigated the potential functions and pathways of Chongmyunggongjin-dan (CMGJD) on Alzheimer’s disease (AD) via network pharmacology analysis.Methods: Using public databases and PubChem database, compounds of CMGJD and their target genes were collected. The putative target genes of CMGJD and known target genes of AD were compared and found the correlation. Then, the network was constructed using Cytoscape 3.9.1. and functional enrichment analysis was conducted based on the Gene Ontology (GO) Biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms.Results: The result showed that total 104 compounds and 1157 related genes were gathered from CMGJD. The network consisted of 1157nodes and 10034 edges. 859 genes were interacted with AD gene set, suggesting that the effects of CMGJD are closely related to AD. Target genes of CMGJD are considerably associated with various pathways including ‘Positive regulation of chemokine production’, ‘Cellular response to toxic substance’, ‘Arachidonic acid metabolic process’, ‘PI3K-Akt signaling pathway’, ‘Metabolic pathways’, ‘IL-17 signaling pathway’ and ‘Neuroactive ligand-receptor interaction’.Conclusion: Through a network pharmacological method, CMGJD was predicted to have high relevance with AD by regulating inflammation. This study could be used as a basis for effects of CMGJD on AD.

Active components and mechanism of Jinwugutong Capsules in treatment of osteoporosis: a study based on UPLC-Q-Exactive-MS/MS combined with network pharmacology

UPLC-Q-Exactive-MS/MS and network pharmacology were employed to preliminarily study the active components and mechanism of Jinwugutong Capsules in the treatment of osteoporosis. Firstly, UPLC-Q-Exactive-MS/MS was employed to characterize the chemical components of Jinwugutong Capsules, and network pharmacology was employed to establish the "drug-component-target-pathway-disease" network. The key targets and main active components were thus obtained. Secondly, AutoDock was used for the molecular docking between the main active components and key targets. Finally, the animal model of osteoporosis was established, and the effect of Jinwugutong Capsules on the expression of key targets including RAC-alpha serine/threonine-protein kinase(AKT1), albumin(ALB), and tumor necrosis factor-alpha(TNF-α) was determined by enzyme-linked immunosorbent assay(ELISA). A total of 59 chemical components were identified from Jinwugutong Capsules, among which coryfolin, 8-prenylnaringenin, demethoxycurcumin, isobavachin, and genistein may be the main active components of Jinwugutong Capsules in treating osteoporosis. The topological analysis of the protein-protein interaction(PPI) network revealed 10 core targets such as AKT1, ALB, catenin beta 1(CTNNB1), TNF, and epidermal growth factor receptor(EGFR). The Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment showed that Jinwugutong Capsules mainly exerted the therapeutic effect by regulating the phosphatidylinositol 3-kinase(PI3K)/protein kinase B(AKT) signaling pathway, neuroactive ligand-receptor interaction, mitogen-activated protein kinase(MAPK) signaling pathway, Rap1 signaling pathway and so on. Molecular docking showed that the main active components of Jinwugutong Capsules well bound to the key targets. ELISA results showed that Jinwugutong Capsules down-regulated the protein levels of AKT1 and TNF-α and up-regulated the protein level of ALB, which preliminarily verified the reliability of network pharmacology. This study indicates that Jinwugutong Capsules may play a role in the treatment of osteoporosis through multiple components, targets, and pathways, which can provide reference for the further research.

Genetic Insights into Obesity and Brain: Combine Mendelian Randomization Study and Gene Expression Analysis.

As a major public-health concern, obesity is imposing an increasing social burden around the world. The link between obesity and brain-health problems has been reported, but controversy remains. To investigate the relationship among obesity, brain-structure changes and diseases, a two-stage analysis was performed. At first, we used the Mendelian-randomization (MR) approach to identify the causal relationship between obesity and cerebral structure. Obesity-related data were retrieved from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and the UK Biobank, whereas the cortical morphological data were from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium. Further, we extracted region-specific expressed genes according to the Allen Human Brian Atlas (AHBA) and carried out a series of bioinformatics analyses to find the potential mechanism of obesity and diseases. In the univariable MR, a higher body mass index (BMI) or larger visceral adipose tissue (VAT) was associated with a smaller global cortical thickness (pBMI = 0.006, pVAT = 1.34 × 10-4). Regional associations were found between obesity and specific gyrus regions, mainly in the fusiform gyrus and inferior parietal gyrus. Multivariable MR results showed that a greater body fat percentage was linked to a smaller fusiform-gyrus thickness (p = 0.029) and precuneus surface area (p = 0.035). As for the gene analysis, region-related genes were enriched to several neurobiological processes, such as compound transport, neuropeptide-signaling pathway, and neuroactive ligand-receptor interaction. These genes contained a strong relationship with some neuropsychiatric diseases, such as Alzheimer's disease, epilepsy, and other disorders. Our results reveal a causal relationship between obesity and brain abnormalities and suggest a pathway from obesity to brain-structure abnormalities to neuropsychiatric diseases.

Identification of a potential novel biomarker in intervertebral disk degeneration by bioinformatics analysis and experimental validation.

Intervertebral disk degeneration (IVDD) is a major cause of low back pain and one of the most common health problems all over the world. However, the early diagnosis of IVDD is still restricted. The purpose of this study is to identify and validate the key characteristic gene of IVDD and analyze its correlation with immune cell infiltration. 3 IVDD-related gene expression profiles were downloaded from the Gene Expression Omnibus database to screen for differentially expressed genes (DEGs). Gene Ontology (GO) and gene set enrichment analysis (GSEA) were conducted to explore the biological functions. Two machine learning algorithms were used to identify characteristic genes, which were tested to further find the key characteristic gene. The receiver operating characteristic curve was performed to estimate the clinical diagnostic value of the key characteristic gene. The excised human intervertebral disks were obtained, and the normal nucleus pulposus (NP) and degenerative NP were carefully separated and cultured in vitro. The expression of the key characteristic gene was validated by real-time quantitative PCR (qRT-PCR). The related protein expression in NP cells was detected by Western blot. Finally, the correlation was investigated between the key characteristic gene and immune cell infiltration. A total of 5 DEGs, including 3 upregulated genes and 2 downregulated genes, were screened between IVDD and control samples. GO enrichment analysis showed that DEGs were enriched to 4 items in BP, 6 items in CC, and 13 items in MF. They mainly included the regulation of ion transmembrane transport, transporter complex, and channel activity. GSEA suggested that the cell cycle, DNA replication, graft versus host disease, and nucleotide excision repair were enriched in control samples, while complement and coagulation cascades, Fc γ R-mediated phagocytosis, neuroactive ligand-receptor interaction, the NOD-like receptor signaling pathway, gap junctions, etc., were enriched in IVDD samples. Furthermore, ZNF542P was identified and tested as key characteristic gene in IVDD samples through machine learning algorithms and showed a good diagnostic value. The results of qRT-PCR showed that compared with normal NP cells, the expression of ZNF542P gene was decreased in degenerated NP cells. The results of Western blot suggested that compared with normal NP cells, the expression of NLRP3 and pro Caspase-1 was increased in degenerated NP cells. Finally, we found that the expression of ZNF542P was positively related to the proportions of T cells gamma delta (γδT cells). ZNF542P is a potential biomarker in the early diagnosis of IVDD and may be associated with the NOD-like receptor signaling pathway and the infiltration of γδT cells.

Transcriptome analysis of Euwallacea interjectus reveals differentially expressed unigenes related to developmental stages and egg laying

Euwallacea interjectus (Curculionidae: Scolytinae) is an ambrosia beetle species in its early stages of research. Therefore, studying the related molecular mechanism associated with the development and egg laid is essential. Transcriptome sequencing was used in this study to compare the gene expression of the beetles at different developmental stages and female adults before and after oviposition. A total of 40,047 annotated unigenes were obtained. There were 4225 differentially expressed unigenes (DEUs) from larva to prepupa stage, 3651 DEUs between prepupa and pupa, 1675 DEUs generated from pupa to adult, and 4762 DEUs between females before and after oviposition. The most significant pathway differences between different development stages and before and after oviposition were selected through functional annotation of DEUs between different stages. Among them, there were many pathways related to protein metabolism including: neuroactive ligand-receptor interaction, endoplasmic reticulum and RNA transport. This study provides valuable information on the molecular regulation mechanism of development and the egg laid of E. interjectus.

Exploring the potential targets of Biling Weitong Granules on visceral hypersensitivity through integration of network pharmacology and in vivo analysis

Ethnopharmacological relevanceBiling Weitong Granules (BLWTG) are a newly developed traditional Chinese medicine prescription based on the ancient prescription Jinlingzi San and Zuojin Wan. It is used for the treatment of functional gastrointestinal disorders (FGIDs) featured as visceral hypersensitivity (VH). However, its active ingredients and protein targets involved still remain unknown. Aim of the studyTo explore the potential targets of BLWTG for the treatment of visceral hypersensitivity. Materials and methodsActive components and their protein targets of BLWTG were screened from TCMSP database and the component-target network were constructed with Cytoscape software. Irritable bowel syndrome (IBS) was the representative disease in this study and information on its linked pathways was obtained from NCBI, Drugbank and Genecard. Target pathways of BLWTG were analyzed through KEGG to verify the correlation with IBS related pathways.Then, the VH mouse models was induced by maternal separation (MS), randomly divided into normal saline (NS),BLWTG1 (low-dosage) and BLWTG2 (high-dosage) group. After intervention, threshold intensity of colorectal distension (CRD) and body weight were measured to evaluate relief of IBS symptoms. Elisa was performed to evaluate 5-HT concentration changes of colon tissues. Flow cytometry was performed to assess changes of colon eosinophils and mast cells proportion. Transcriptome sequencing was employed to analyze changes of pathways and differential genes. Results199 protein targets and 132 active components of BLWTG were identified. KEGG analysis revealed the overlap between BLWTG target pathways and IBS related pathways such as neuroactive ligand-receptor interaction, tryptophan metabolism and inflammatory reaction. 34 genes were not only BLWTG target proteins but also recognized targets for treating IBS.After maternal separation (MS), the mice showed a significant decrease in threshold intensity of CRD, a progressive decrease in body weight and an increase of 5-HT concentration of colon tissue. The proportion of mast cells and eosinophils in the colon increased. Differential genes including Hp,Ido1 and Aqp7 were significantly increased in MS mice group and IBS-related pathways were upregulated. After treatment of BLWTG, threshold intensity of CRD and body weight were significantly improved and IBS related pathways were downregulated. In addition, among BLWTG protein targets, Il1b,Tnf,Adrb1 and Nos2 were found upregulated in MS+NS mice and downregulated after BLWTG intervention through combination of transcriptome sequencing. ConclusionsIn maternal separation-induced mouse models, BLWTG could alleviate visceral hypersensitivity, possibly through downregulation of 5-HT concentration and eosinophils and mast cells proportion in colon and critical pathways such as neuroactive ligand-receptor pathway. Potential targets of BLWTG including Il1b,Tnf,Adrb1 and Nos2 were found through integration of network pharmacology database and transcriptome sequencing, providing evidence for further study on mechanisms underlying visceral hypersensitivity.

Study on Mechanism of Shenqi Dihuang Decoction in Treating Diabetic Nephropathy Based on Network Pharmacology

Objective: To explore the mechanism of Shenqi Dihuang Decoction in treating diabetic nephropathy based on network pharmacology. Methods: The component targets of Shenqi Dihuang Decoction and diabetic nephropathy (DKD) targets were searched and screened by network database. Using Cytoscape3.7.2 software to construct a network of traditional Chinese medicine components-targets; The protein-protein interaction network (PPI) of Shenqi Dihuang Decoction for CRF treatment was constructed using STRING database, and the core targets were found out through topological analysis. Finally, biological pathway and enrichment analysis were carried out on drug-disease intersection targets. Results: A total of 106 active ingredients of Shenqi Dihuang Decoction were collected. 1532 corresponding targets; DKD disease targets 533; There are 48 common targets for drug components and diseases. Topological analysis was performed with a Degree value 2 times (14.3) higher than the average, and 4 key core targets were finally obtained. Biological process and enrichment analysis show that the prescription mainly involves 13 biological processes, 4 KEGG pathways and 3 typical pathways in treating DKD, mainly involving cell response to hormone stimulation, followed by biological processes such as neuroactive ligand-receptor interaction KEGG pathway, blood circulation, cell response to nitrogen compounds, chemical synaptic transmission, etc. Conclusion: Shenqi Dihuang Decoction mainly acts on PTGS2, NR3C1, NOS3, ESR1 and other targets. Its targets are many and its mechanism is complex. It may play a role mainly through the biological process of regulating the response degree of cells to hormone stimulation.

Transcriptome analysis reveals dysregulation of inflammatory and neuronal function in dorsal root ganglion of paclitaxel-induced peripheral neuropathy rats.

Chemotherapy-induced peripheral neuropathy (CIPN) is the most common side-effect of anti-cancer therapy. To date, there are no clinically effective analgesics that could prevent and treat CIPN. However, the exact pathogenesis of CIPN is still unclear. In the present study, we use the paclitaxel-induced peripheral neuropathy (PIPN) model, aiming to better understand the transcriptomic level of the Dorsal root ganglia (DRG) neurons in rats with PIPN. mRNA from each DRG sample was reverse transcribed to cDNA and sequenced using next-generation high throughput sequencing technology. Quantitative RT-PCR verification was used to confirm the identified Differentially expressed genes (DEGs) in the DRG of PIPN rats. RNAseq results have identified 384 DEGs (adjusted P-value < 0.05; fold change ≥ 2) in the DRG of rats 14days after paclitaxel injection in total, including 97 up-regulated genes, and 287 down-regulated genes. GO analysis revealed that these DEGs were majorly involved in neuropeptide activity, chemokine receptor activity, defense response, and inflammatory response. Kyoto Encyclopedia of Gene and Genomes analysis showed that neuroactive ligand-receptor interaction and cytokine-cytokine receptor interaction were involved in sensory neurons of rats with PIPN. Besides, comparison analysis identified that 11 DEGs in the PIPN model are shared with either inflammatory pain (Ces1d, Cfd, Retn, and Fam150b) or neuropathic pain (Atf3, Csrp3, Ecel1, Gal, Sprr1a, Tgm1, and Vip). Quantitative RT-PCR results also confirmed the validation of the RNAseq data. These results suggested that neuroactive ligand-receptor interaction and cytokine-cytokine receptor interaction are majorly involved in sensory neurons of rats with PIPN. Immune, inflammatory responses and neuron functional changes are the major pathogenesis of PIPN. Paclitaxel-induced peripheral neuropathy has shared characteristics with both inflammatory pain and neuropathic pain.

Transcriptome analysis of the uterovaginal junction containing sperm storage tubules in heat-stressed breeder hens

Sperm storage tubules (SSTs) in the uterovaginal junction (UVJ) of the oviduct are major sites of sperm storage after artificial insemination or mating. Female birds may regulate sperm motility in the UVJ. Heat stress can decrease the reproductive ability of broiler breeder hens. However, its effects on UVJ remain unclear. Changes in gene expression aid in understanding heat stress-affected molecular mechanisms. Herein, we wanted to conduct a comparative transcriptomic analysis to identify the differentially expressed genes (DEGs) in the UVJ of breeder hens under thermoneutral (23°C) and heat stress (36°C for 6 h) conditions. The results indicated that cloacal temperatures and respiratory rates were significantly increased in heat-stressed breeder hens (P < 0.05). Total RNA was extracted from the hen UVJ tissues containing SSTs after heat exposure. Transcriptome analysis identified 561 DEGs, including 181 upregulated DEGs containing heat shock protein (HSP) transcripts and 380 downregulated DEGs containing immune-related genes, such as interleukin 4-induced 1, radical S-adenosyl methionine domain containing 2, and 2'-5'-oligoadenylate synthetase like, in heat-stressed hens. Gene Ontology analysis revealed the significantly enriched terms involving HSPs. Kyoto Encyclopedia of Genes and Genomes analysis identified 9 significant pathways, including the protein processing in endoplasmic reticulum (11 genes including HSPs), neuroactive ligand-receptor interaction (13 genes including luteinizing hormone/choriogonadotropin receptor), biosynthesis of amino acids (4 genes including tyrosine aminotransferase), ferroptosis (3 genes including heme oxygenase 1), and nitrogen metabolism (carbonic anhydrase [CA]-12 and CA6) pathways. Protein-protein interaction network analysis of DEGs revealed 2 large networks, one containing upregulated HSPs and the other containing downregulated interferon-stimulating genes. Overall, heat stress inhibits innate immunity in the UVJ tissues of broiler chickens, and heat-stressed chickens protect their cells by increasing the expression levels of HSPs. The identified genes are potential candidates for further exploration of the UVJ in heat-stressed hens. The identified molecular pathways and networks increase our understanding of the sperm storage reservoirs (UVJ containing SSTs) within the reproductive tract and may be used to prevent heat stress-induced fertility loss in breeder hens.

Integration of non-targeted metabolomics with network pharmacology deciphers the anxiolytic mechanisms of Platycladi Semen extracts in CUMS mice

Ethnopharmacological relevancePlatycladi Semen was recorded in Shen Nong's Herbal Classic and was considered a herbal medicine with low toxicity after long-term medication. Multiple traditional Chinese medicine prescriptions containing Platycladi Semen have been used to treat insomnia. Modern clinical practitioners commonly use Platycladi Semen to treat anxiety disorders, but there are few studies on its composition and anxiolytic mechanisms. Aim of the studyTo describe the main components of Platycladi Semen and investigate its anxiolytic effects and mechanisms. Materials and methodsThe main components of Platycladi Semen were characterized by liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). The anxiolytic effects of oral Platycladi Semen were evaluated in chronic unpredictable mild stress (CUMS) induced mice. To explore the anxiolytic mechanisms of Platycladi Semen, serum non-targeted metabolomics combined with network pharmacology and molecular docking was performed. ResultsFourteen compounds were identified in the 50% methanol extract and 11 fatty acid derivatives were identified in the methyl-esterified fatty oil of Platycladi Semen. In CUMS mice, both the aqueous extract and fatty oil of Platycladi Semen had anxiolytic effects, which were shown by the increase in the time and frequency of mice entering the open arm in the elevated plus maze (EPM) experiment. Through serum non-targeted metabolomics, 34 differential metabolites were identified, and lipid metabolic pathways such as sphingolipid metabolism, steroidogenesis, alpha-linoleic acid, and linoleic acid metabolism were enriched. Through network pharmacology, 109 targets of the main components in Platycladi Semen were identified, and the ‘neuroactive ligand-receptor interaction’ and ‘lipid metabolism’ were enriched. The molecular docking results showed that the main components in Platycladi Semen could bind to the key targets such as peroxisome proliferator-activated receptor delta (PPARD), peroxisome proliferator-activated receptor alpha (PPARA), fatty acid binding protein 5 (FABP5), fatty acid binding protein 3 (FABP3), peroxisome proliferator-activated receptor gamma (PPARG), arachidonate 5-lipoxygenase (ALOX5) and fatty acid amide hydrolase (FAAH). ConclusionThis study indicated that Platycladi Semen has anxiolytic effects, and the anxiolytic mechanisms may be the regulation of lipid metabolism and the neuroactive ligand-receptor interaction.

RETRACTED ARTICLE: Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies

Background Chronic morphine usage induces lasting molecular and microcellular adaptations in distinct brain areas, resulting in addiction-related behavioural abnormalities, drug-seeking, and relapse. Nonetheless, the mechanisms of action of the genes responsible for morphine addiction have not been exhaustively studied.MethodsWe obtained morphine addiction-related datasets from the Gene Expression Omnibus (GEO) database and screened for Differentially Expressed Genes (DEGs). Weighted Gene Co-expression Network Analysis (WGCNA) functional modularity constructs were analyzed for genes associated with clinical traits. Venn diagrams were filtered for intersecting common DEGs (CDEGs). Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for functional annotation. Protein–protein interaction network (PPI) and CytoHubba were used to screen for hub genes. Potential treatments for morphine addiction were figured out with the help of an online database.ResultsSixty-five common differential genes linked to morphine addiction were identified, and functional enrichment analysis showed that they were primarily involved in ion channel activity, protein transport, the oxytocin signalling pathway, neuroactive ligand-receptor interactions, and other signalling pathways. Based on the PPI network, ten hub genes (CHN2, OLIG2, UGT8A, CACNB2, TIMP3, FKBP5, ZBTB16, TSC22D3, ISL1, and SLC2A1) were checked. In the data set GSE7762, all of the Area Under Curve (AUC) values for the hub gene Receiver Operating Characteristic (ROC) curves were greater than 0.8. We also used the DGIdb database to look for eight small-molecule drugs that might be useful for treating morphine addiction.ConclusionsThe hub genes are crucial genes associated with morphine addiction in the mouse striatum. The oxytocin signalling pathway may play a vital role in developing morphine addiction.