Protein-protein Interaction Network Research Articles

Comparative proteomic analysis of male and female androgenetic alopecia: elucidating gender-specific molecular patterns.

This study presents a comprehensive comparative proteomic analysis aimed at elucidating the molecular mechanisms underlying male androgenetic alopecia (AGA) and female AGA. Scalp samples from both male AGA and female AGA patients, along with their respective normal controls, were subjected to proteomic analysis, followed by bioinformatics investigations. Our findings revealed distinct proteomic profiles between male AGA and female AGA, with a total of 68 differentially expressed proteins identified in male AGA and 84 in female AGA. Among these, specific proteins were altered in male AGA and female AGA, highlighting the sex-specific molecular pathways involved in the pathogenesis of pattern hair loss. Protein-protein interaction network analyses further delineated the most impacted biological processes, including cytoskeleton organization, stress response, and metabolic pathways, with particular emphasis on the differing altered stress responses and metabolic states associated with hair loss between sexes. Our study not only uncovered the complex molecular landscape of male AGA and female AGA but also identified potential biomarkers and therapeutic targets, offering new insights into the sex-specific pathogenesis of pattern hair loss.

Unveiling the genetic link and pathogenesis between psoriasis and IgA nephropathy based on Mendelian randomization and transcriptome data analyses.

It has been reported that many people with psoriasis have been diagnosed with secondary IgA nephropathy (IgAN). However, the mechanisms behind the association between psoriasis and IgAN have not been well clarified. The connection between psoriasis and IgAN deserves deeper exploration. Mendelian randomization (MR) analysis would be employed to explore the link of causality between IgAN and psoriasis, psoriasis vulgaris, other and unspecified psoriasis, guttate psoriasis, and arthropathic psoriasis. Transcriptomic analyses were carried out against the Gene Expression Omnibus databases. We identified crosstalk genes through the analysis of Differentially expressed genes and weight gene co-expression network analysis. Functional annotations were enriched for these crosstalk genes. Subsequently, we established a protein-protein interaction network, and candidate genes would be discovered through the utilization of the MCODE and CytoHubba plug-in applications. Lastly, the predictive efficacy of these genes was examined via creating receiver operating characteristic curves. The MR analysis suggested that psoriasis vulgaris patients were at a higher risk for IgAN. [OR = 1.040, 95%CI (1.005,1.076), p = 0.026 < 0.05]. Additionally, arthropathic psoriasis may augment the incidence of IgAN [OR = 1.081, 95%CI (1.040-1.124), p < 0.01] in the European population. Through the analysis of DEGs and WGCNA, we identified 12 significant genes (NETO2, RRM2, SLAMF7, GBP1, KIF20A, CCL4, MMP1, IL1β, NDC80, CXCL9, C15orf48, GSTA3), which may be potential crosstalk genes between the two diseases. Then, the functional annotation results indicated that the crosstalk genes seemed primarily involved in immune and inflammatory responses. By establishing the PPI network, we further discovered that CXCL9, IL1β, CCL4, and MMP1 play a vital part in psoriasis and IgAN, and all have good diagnostic values. Our MR analysis provided evidence that genetic vulnerability to IgAN may be associated with an elevated risk of psoriasis vulgaris and arthropathic psoriasis respectively among Europeans. Doctors should be aware of these associations when patients with psoriasis present with renal dysfunction, especially those with psoriasis vulgaris and arthropathic psoriasis. Chronic inflammation, drug effects, and immunity may contribute to the generation and development of both diseases. IL1β, CXCL9, CCL4, and MMP1 may be core biomarkers for psoriasis and IgAN.

Proteome-wide Mendelian randomization provides novel insights into the pathogenesis and druggable targets of osteoporosis

BackgroundWith the aging population, the prevalence and impact of osteoporosis are expected to rise, and existing anti-osteoporosis agents have limitations due to adverse events. This study aims to discover novel drug targets for osteoporosis.MethodsThe protein data were obtained from the latest proteome-wide association studies (PWAS) including 54, 219 participants. The osteoporosis data were extracted from a GWAS meta-analysis, characterized by heel bone mineral density (HBMD) comprising 426,824 individuals. Mendelian randomization (MR) was the primary approach used to establish genetic causality between specific traits. Summary-data-based MR (SMR), colocalization analysis, heterogeneity test, and external validation were applied to ensure the findings were reliable. The underlying mechanisms behind these causal associations were investigated by additional analyses. Finally, the druggability of the identified proteins was assessed.ResultsAfter Bonferroni correction, a total of 84 proteins were found to have a genetic association with osteoporosis. With strong colocalization evidence, proteins such as ACHE, HS6ST1, LRIG1, and LRRC37A2 were found to negatively influence HBMD, whereas CELSR2, CPE, FN1, FOXO1, and FSHB exhibited a positive association with HBMD. No significant heterogeneity was found. Additionally, CELSR2, FN1, FSHB, HS6ST1, LRIG1, and LRRC37A2 were replicated in the external validation. The effect of FSHB on HBMD was more pronounced in females compared to males. Interestingly, ACHE, LRIG1, FN1, and FOXO1 were observed to partially act on HBMD through BMI. Phewas analysis indicated that CPE and FOXO1 did not have genetic associations with any phenotypes other than osteoporosis. FN1 was highlighted as the most significant protein by protein-protein interaction network analysis.ConclusionIn conclusion, this study offers valuable insights into the role of specific proteins in the development of osteoporosis, and underscores potential therapeutic targets. Future studies should emphasize exploring these causal relationships and elucidating their underlying mechanisms.

Investigating the Role of Hub Calcification Proteins in Atherosclerosis via Integrated Transcriptomics and Network-Based Approach

Atherosclerosis (AS) is a chronic inflammatory condition of the arteries, characterized by plaque formation that can restrict blood flow and lead to potentially fatal cardiovascular events. Given that AS is responsible for a quarter of global deaths, this study aimed to develop a systematic bioinformatics approach to identify biomarkers and regulatory targets involved in plaque development, with the goal of reducing cardiovascular disease risk. AS-specific mRNA expression profiles were retrieved from a publicly accessible database, followed by differentially expressed genes (DEGs) identification and AS-specific weighted gene co-expression network (WGCN) construction. Thereafter, calcification and atherosclerosis-specific (CASS) DEGs were utilized for protein–protein interaction network (PPIN) formation, followed by gene ontology (GO) term and pathway enrichment analyses. Lastly, AS-specific 3-node miRNA feed-forward loop (FFL) construction and analysis was performed. Microarray datasets GSE43292 and GSE28829 were obtained from gene expression omnibus (GEO). A total of 3785 and 6176 DEGs were obtained in case of GSE28829 and GSE43292; 3256 and 5962 module DEGs corresponding to GSE28829 and GSE43292 were obtained from WGCN. From a total of 54 vascular calcification (VC) genes, 20 and 29 CASS-DEGs corresponding to GSE28829 and GSE43292 were overlapped. As observed from FFL centrality measures, the highest-order subnetwork motif comprised one TF (SOX7), one miRNA (miR-484), and one mRNA (SPARC) in the case of GSE28829. Also, in the case of GSE43292, the highest-order subnetwork motif comprised one TF (ESR2), one miRNA (miR-214-3p), and one mRNA (MEF2C). These findings have important implications for developing new therapeutic strategies for AS. The identified TFs and miRNAs may serve as potential therapeutic targets for treating atherosclerotic plaques, offering insights into the molecular mechanisms underlying the pathogenesis and highlighting new avenues for research and treatment.

Identification of Specific microRNAs in Adipose Tissue Affected by Lipedema

Lipedema is a chronic disorder affecting women with a 10% incidence worldwide. It is often confused with obesity. This study was undertaken to study microRNAs in lipedema tissue assessed by direct hybridization using the robust n-counter flex DX CE-IVD platform. The mean age of the subjects participating in the study was 40.29 (±12.17). The mean body weight and BMI were 67.37 (±10.02) and 25.75 (±4.10), respectively. The lipedema stages included were I and II. The differential expressed human (hsa)-miRNAs were determined according to a log2 fold-change (LFC) of 0.5 and p value &lt; 0.05. To these, increased expression of hsa-let-7g-5p was evident, as well as reduced levels of hsa-miR-371a-5p, -4454+7975, -365a+b-3p, -205-5p, -196a-5p, -4488, -2116-5p, -141-3p, -208a-3p, -302b-3p, 374a-5p, and -1297. Then, several bioinformatics tools were used to analyze microarray data focusing on validated target genes in silico. KEGG and Gene Ontology (GO) pathway enrichment analysis was conducted. Furthermore, the protein–protein interaction and co-expression network were analyzed using STRING and Cytoscape, respectively. The most upregulated miRNA mainly affected genes related to cell cycle, oocyte meiosis, and inflammatory bowel disease. The downregulated microRNAs were related to endocrine resistance, insulin resistance, hypersensitivity to AGE-RAGEs, and focal adhesion. Finally, we validated by RT-PCR the upregulated hsa-let-7g-5p and two down-regulated ones, hsa-miR-205-5p and hsa-miR-302b-3p, confirming microarray results. In addition, three mRNA target miRNAs were monitored, SMAD2, the target of the hsa-let-7g-5p, and ESR1 and VEGFA, the target of hsa-miR-205-5p and hsa-miR-302b-3p, respectively. Our results open a new direction for comprehending biochemical mechanisms related with the pathogenesis of lipedema, shedding light on this intricate pathophysiological condition that could bring to light possible biomarkers in the future.

Insights into the Therapeutic Potential of Active Ingredients of Citri Reticulatae Pericarpium in Combatting Sarcopenia: An In Silico Approach

Sarcopenia is a systemic medical disorder characterized by a gradual decline in muscular strength, function, and skeletal muscle mass. Currently, there is no medication specifically approved for the treatment of this condition. Therefore, the identification of new pharmacological targets may offer opportunities for the development of novel therapeutic strategies. The current in silico study investigated the active ingredients and the mode of action of Citri Reticulatae Pericarpium (CRP) in addressing sarcopenia. The active ingredients of CRP and the potential targets of CRP and sarcopenia were determined using various databases. The STRING platform was utilized to construct a protein–protein interaction network, and the key intersecting targets were enriched through the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. Molecular docking was used to determine the binding interactions of the active ingredients with the hub targets. The binding affinities obtained from molecular docking were subsequently validated through molecular dynamics simulation analyses. Five active ingredients and 45 key intersecting targets between CRP and sarcopenia were identified. AKT1, IL6, TP53, MMP9, ESR1, NFKB1, MTOR, IGF1R, ALB, and NFE2L2 were identified as the hub targets with the highest degree node in the protein–protein interaction network. The results indicated that the targets were mainly enriched in PIK3-AKT, HIF-1, and longevity-regulating pathways. The active ingredients showed a greater interaction affinity with the hub targets, as indicated by the results of molecular docking and molecular dynamics simulations. Our findings suggest that the active ingredients of Citri Reticulatae Pericarpium, particularly Sitosterol and Hesperetin, have the potential to improve sarcopenia by interacting with AKT1 and MTOR proteins through the PI3K-AKT signaling pathway.

Design and development of dual targeting CAR protein for the development of CAR T-cell therapy against KRAS mutated pancreatic ductal adenocarcinoma using computational approaches

Mutant KRAS promotes the proliferation, metastasis, and aggressiveness of various cancers including pancreatic ductal adenocarcinoma (PDAC), non-small cell lung cancer (NSCLC), and colorectal adenocarcinoma (CRC) respectively. Mutant KRAS therapeutics are limited, while Sotorasib and Adagrasib were the only FDA-approved drugs for the treatment of KRASG12C mutated NSCLC. Chimeric antigen receptor (CAR) T-cell therapy has been emerged as an effective strategy against hematological malignancies and being extended towards solid cancers including PDAC. mesothelin (MSLN) and Carcinoembryonic Antigen (CEA) were reported to be highly overexpressed in KRAS-mutated PDAC. Meanwhile, in clinical trials, several CAR T-cell therapy studies are mainly focused towards these two cancer antigens in PDAC, however, the dual targeting of these two neoantigens is not reported. In the present study, we have designed and developed a novel dual-targeting CAR protein by employing various bioinformatics approaches such as functional analysis (antigenicity, allergenicity, antigen binding sites & signalling cascades), qualitative analysis (physicochemical, prediction, refinement & validation of 2D and 3D structures), molecular docking, and in silico cloning. Our results revealed that the designed CAR protein specifically binds with both MSLN & CEA with significant binding affinities, and was predicted to be stable & non-allergenic. Additionally, the protein–protein interaction network reveals the T-cell mediated antitumor responses of each domain in the designed CAR. Conclusively, we have designed and developed a dual targeting (MSLN & CEA) CAR protein towards KRAS-mutated PDAC using computational approaches. Alongside, we further recommend to engineer this designed CAR in T-cells and evaluating their therapeutic efficiency in in vitro and in vivo studies in the near future.

Unveiling novel prognostic biomarkers and therapeutic targets for HBV-associated hepatocellular carcinoma through integrated bioinformatic analysis.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths globally, with limited treatment options. The goal of this study was to use integrated bioinformatic analysis to find possible biomarkers for prognosis and therapeutic targets for hepatitis B (HBV)-associated HCC. Three microarray datasets (GSE84402, GSE121248, and E-GEOD-19665) from patients with HBV-associated HCC were combined and analyzed. We identified differentially expressed genes (DEGs) and performed pathway enrichment analysis. We constructed protein-protein interaction networks to identify hub genes. We identified a total of 374 DEGs, which included 90 up-regulated and 284 down-regulated genes. Pathway enrichment analysis revealed associations with cell cycle, oocyte meiosis, and the p53 signaling pathway for up-regulated DEGs. Twenty hub genes were identified, and 9 of them (ZWINT, MELK, DLGAP5, BIRC5, AURKA, HMMR, CDK1, TTK, and MAD2L1) were validated using the Cancer Genome Atlas data and Kaplan-Meier survival analysis. These genes were significantly associated with a poor prognosis in HCC patients. Our research shows that ZWINT, MELK, DLGAP5, BIRC5, AURKA, HMMR, CDK1, TTK, and MAD2L1 may be useful for predicting how HBV-associated HCC will progress and for finding new ways to treat it. In addition to these further studies are needed to elucidate the functions of the remaining 11 identified hub genes (RRM2, NUSAP1, PBK, CCNB1, CCNB2, BUB1B, NEK2, CENPF, ASPM, TOP2A, and BUB1) in HCC development and progression.

A Network Pharmacology Study on Mechanism of Total Flavonoids of Hippophae Rhamnoides in Treating Allergic Dermatitis via Regulation of IL-17 Signaling Pathways

Objective: This study aims to investigate the active ingredients and potential mechanisms of Total Flavonoids of Hippophae (TFH) in the treatment of Allergic Dermatitis (AD) using network pharmacology and molecular docking. Methods: The effective components and targets of TFH were identified using the TCMSP, Pub- Chem, and Pharmmapper databases. AD-related targets were screened through GeneCards, OMIM, and TTD databases, leading to the identification of TFH anti-AD related targets. The STRING database was utilized to obtain protein interaction relationships, and Cytoscape 3.9.0 software was employed to construct the protein-protein interaction network. GO and KEGG enrichment analyses were conducted to elucidate the biological processes and pathways involved. Molecular docking between key components and key targets was verified using AutoDock Tools 1.5.6 software. Results: The key components identified for anti-AD activity were Quercetin, Kaempferol, Cianidanol, and Epicatechin, while the key targets included MAPK8, MAPK10, MAPK14, AKT1, SRC, and EGFR. GO analysis indicated that TFH's anti-AD effects are primarily associated with hormone regulation, cellular processes, response to stimuli, organelles, and cytoplasm. KEGG enrichment analysis suggested that the key pathways involved are pathways in cancer, lipid and atherosclerosis, and the IL-17 signaling pathway, with a significant emphasis on the IL-17 signaling pathway. Molecular docking results demonstrated that the key active ingredients exhibited strong binding activity with all the key targets, with the highest binding affinities observed between kaempferol and MAPK14, epicatechin and MAPK14, and quercetin and AKT1. Conclusion: TFH exerts therapeutic effects on atopic dermatitis through multi-component, multitarget, and multi-pathway mechanisms involving inflammatory response, immune regulation, and apoptosis. This study provides valuable insights for the further development of drugs specifically targeting AD.

Integrating network pharmacology, molecular docking, and experimental validation to reveal the mechanism of Radix Rehmanniae in psoriasis.

Radix Rehmanniae (RR) plays an important role in treating psoriasis. However, the active compounds of RR and potential mechanisms are unclear. The current study was designed to investigate the potential active ingredients, targets, and mechanisms of RR in treating psoriasis through network pharmacology, molecular docking, and vitro experiments. Initially, the TCMSP database and literature retrieval were used to access the active ingredients of RR. The psoriasis target proteins were obtained from Therapeutic Target Database, OMIM, GeneCards, and DrugBank databases. The target proteins were then converted into target genes using Uniprot. Secondly, overlapping genes were obtained through Venn online tool. Then, protein-protein interactions network diagram is finished by STRING database. Next, Cytoscape software was used to acquire the top 10 hub proteins; gene ontology and Kyoto encyclopedia of genes and genomes enrichment analysis were then used to predict possible mechanisms. Afterwards, molecular docking validation of the active ingredients with the main targets was performed by AutoDock software. Finally, lipopolysaccharides induced RAW264.7, to assess the effects and molecular mechanisms by MTT, RT-qPCR, and Western blot assays. Overall, there are 20 effective compounds and 33 targets involved in biological processes including apoptosis, intracellular signaling, vasodilation, and mitogen-activated protein kinase (MAPK) signaling cascade. The docking results showed strong binding capacity between the active ingredients and targets. We verified aucubin as the key active ingredient, tumor necrosis factor α, and IL6 as the core targets, and focused on the p38MAPK protein pathway. Cellular experiments showed that aucubin down-regulated the phosphorylated p38MAP protein and reduced the expression of tumor necrosis factor α mRNA, IL6 mRNA, and IL1βmRNA. In summary, RR is featured with multicomponent, multi-target, and multi-pathway in treating psoriasis; the preliminary mechanism may be associated with the down-regulation of p38MAPK phosphorylation and curbing the expression of inflammatory factor by aucubin. This paper provides the scientific basis for Traditional Chinese medicine treating psoriasis.

Key genes and pathways in the molecular landscape of pancreatic ductal adenocarcinoma: A bioinformatics and machine learning study

Pancreatic ductal adenocarcinoma (PDAC) is recognized for its aggressive nature, dismal prognosis, and a notably low five-year survival rate, underscoring the critical need for early detection methods and more effective therapeutic approaches. This research rigorously investigates the molecular mechanisms underlying PDAC, with a focus on the identification of pivotal genes and pathways that may hold therapeutic relevance and prognostic value. Through the construction of a protein-protein interaction (PPI) network and the examination of differentially expressed genes (DEGs), the study uncovers key hub genes such as CDK1, KIF11, and BUB1, demonstrating their substantial role in the pathogenesis of PDAC. Notably, the dysregulation of these genes is consistent across a spectrum of cancers, positing them as potential targets for wide-ranging cancer therapeutics. This study also brings to the fore significant genes encoding intrinsically disordered proteins, in particular GPRC5A and KRT7, unveiling promising new pathways for therapeutic intervention. Advanced machine learning techniques were harnessed to classify PDAC patients with high accuracy, utilizing the key genetic markers as a dataset. The Support Vector Machine (SVM) model leveraged the hub genes to achieve a sensitivity of 91 % and a specificity of 85 %, while the RandomForest model notched a sensitivity of 91 % and specificity of 92.5 %. Crucially, when the identified genes were cross-referenced with TCGA-PAAD clinical datasets, a tangible correlation with patient survival rates was discovered, reinforcing the potential of these genes as prognostic biomarkers and their viability as targets for therapeutic intervention. This study's findings serve as a potent testament to the value of molecular analysis in enhancing the understanding of PDAC and in advancing the pursuit for more effective diagnostic and treatment strategies.

Identification of hub genes through integrated single-cell and microarray transcriptome analysis in osteoarthritic meniscus

BackgroundOsteoarthritis (OA) is marked by the progressive degradation of joint cartilage and subchondral bone. The precise molecular mechanisms driving meniscus deterioration in OA, especially at the single-cell level, remain poorly understood.MethodWe analyzed two datasets from the GEO database, GSE220243 and GSE98918, focusing on meniscus tissue sequencing data from OA and non-OA patients. The standard Seurat procedure was employed to process single-cell data and identify differentially expressed genes (DEGs). Immune cell infiltration was assessed using the Microenvironment Cell Populations (MCP) counter and CIBERSORT algorithms. For the microarray data, DEGs were identified with the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The overlapping DEGs from both datasets were imported into Cytoscape to generate protein-protein interaction (PPI) networks and identify hub genes. Transcription factor (TF) and miRNA interaction networks were analyzed using NetworkAnalyst, and gene-related predictive drugs were enriched through the DSigDB platform.ResultAfter quality control, 34,763 cells from the OA patients and 34,145 cells from the healthy controls were analyzed. UMAP identified and SingleR annotated 14 cell clusters. The 10 largest cell clusters were selected for further analysis. The OA group exhibited a notable increase in macrophages and a reduction in cytotoxic lymphocytes and endothelial cells in the meniscus. In GSE98918, 220 DEGs were identified, and the MCODE plug-in in Cytoscape pinpointed a key module containing 12 candidate genes. The MCC methodfiltered the top 20 DEGs in each GSE220243 cluster. Overlapping DEGs from GSE220243 and GSE98918 identified COL1A1, COL3A1, COL5A2, COL6A3, LOX, and VEGFA as significantly decreased in OA, with COL3A1, COL5A2, LOX, and VEGFA upregulated in meniscal chondrocytes. The interaction network highlighted 3 key miRNAs and 13 shared TFs. Ten gene-related predictive drug molecules were identified.ConclusionThis research highlights crucial genes in the OA meniscus and uncovers their differing regulatory patterns between chondrocytes and non-chondrocytes. These findings enhance our understanding of the molecular mechanisms driving OA pathogenesis and aid in identifying potential drug targets.

Application of Network Pharmacology, Molecular Docking, and In Vitro Experimental Evaluation to Decipher the Anti-Inflammatory Mechanisms of Cirsium japonicum

Cirsium japonicum, a traditional herb, exhibits significant anti-inflammatory activity. However, the main components and potential mechanisms of C. japonicum remain unclear. The aim of this study is to investigate the anti-inflammatory mechanism of Cirsium japonicum through network pharmacology and cellular experiments. The effective components of and potential targets for the anti-inflammatory activity of C. japonicum were identified using a traditional Chinese medicine systematic pharmacology database, the TCMSP analysis platform, and the GeneCards database. The drug–component–target–disease network diagram was constructed using Cytoscape 3.8.0 software, while the protein interaction network diagram was created using the STRING database and Cytoscape 3.8.0 software. Gene ontology (GO) enrichment and KEGG pathway enrichment analysis were carried out using the DAVID database. Molecular docking between key targets and active components was constructed with AutoDock 4.2.6 software to determine the best binding target. The results revealed that 14 active components of C. japonicum targeted 171 anti-inflammatory proteins. GO function enrichment analysis yielded 173 items, while KEGG pathway enrichment analysis identified 48 signaling pathways related to inflammation regulation. Molecular docking showed a strong affinity of sitosterol, stigmasterol, and other components with key targets such as peroxisome proliferator-activated receptor α recombinant protein (PPARA) and cyclooxygenase-2 (PTGS2). Vanillin, one active ingredient of C. japonicum, inhibited the release of lipopolysaccharide (LPS)-induced inflammatory factors in RAW264.7 cells. These findings suggest that C. japonicum may exert its anti-inflammatory effects by modulating the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) signal pathway (PI3K-Akt) and apoptin signal pathway, highlighting the multi-component, multi-target, and multi-channel molecular mechanism underlying its anti-inflammatory properties. Finally, the anti-inflammatory effect of vanillin, an effective component of C. japonicum, was verified by cell experiments. This study provides a new understanding of the pharmacological mechanisms of C. japonicum in the treatment of inflammatory conditions.

Transcriptome analysis identifies potential molecular mechanisms for growth of fast muscle in Chinese perch juvenile

Chinese perch (Siniperca chuatsi) is an important commercial fish species in China. Understanding the molecular mechanisms of growth and development of skeletal muscle is helpful for selection breeding and improving the growth rate of Chinese perch. We analyzed histological and transcriptomic differences in fast muscle of Chinese perch between 30 days post hatching (dph) and 60 dph using histological sections and high-throughput RNA-Seq. The results showed that the diameter of muscle fibers in 30 dph Chinese perch was mainly distributed in range of 30 − 40 μm, and that of 60 dph was primarily in the range of 40 − 50 μm. 34 differentially expressed genes (DEGs) were identified in the fast muscle of Chinese perch between 30 and 60 dph, of which 9 were up-regulated and 25 were down-regulated (60 dph vs 30 dph). The DEGs, including MYH4, ENO3, Bag3, krt13 and krt18, are associated with muscle cell differentiation and fusion in Chinese perch. The analysis of the protein–protein interaction network of DEGs revealed that FOS, junb and EGR1 may involve in the development of fast muscle. KEGG enrichment results showed that the up-regulated genes in the 60 dph were associated with several pathways related to metabolism and protein synthesis, such as glycosphingolipid biosynthesis and aminoacyl-tRNA biosynthesis. The results suggest that the development of fast muscle in Chinese perch from 30 to 60 dph is accompanied by an increase in muscle fiber diameter and changes in gene expression related to muscle cell differentiation and protein synthesis.Abbreviations: DEGs, differentially expressed genes; dph, days post hatching; FC, fold change; FDR, False Discovery Rate; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; MyHCs, Myosin heavy chains; qRT-PCR, quantitative real-time PCR.

Integrative Network Pharmacology, Molecular Docking, and Dynamics Simulations Reveal the Mechanisms of Cinnamomum tamala in Diabetic Nephropathy Treatment: An In Silico Study

Diabetic nephropathy (DN) is a serious diabetes-related complication leading to kidney damage. Cinnamomum tamala (CT), traditionally used in managing diabetes and kidney disorders, has shown potential in treating DN, although its active compounds and mechanisms are not fully understood. This study aims to identify CT’s bioactive compounds and explore their therapeutic mechanisms in DN. Active compounds in CT were identified using the Indian Medicinal Plants, Phytochemicals and Therapeutics database, and their potential targets were predicted with PharmMapper. DN-related targets were sourced from GeneCards, and therapeutic targets were identified by intersecting the compound–target and disease–target data. Bioinformatics analyses, including the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment studies, were performed on these targets. A protein–protein interaction network was constructed using STRING and Cytoscape. Molecular docking and dynamics simulations validated the most promising compound–target interactions. Six active compounds in CT were identified, along with 347 potential therapeutic targets, of which 70 were DN-relevant. Key targets like MMP9, EGFR, and AKT1 were highlighted, and the PPAR and PI3K-AKT signaling pathways were identified as the primary mechanisms through which CT may treat DN. CT shows promise in treating DN by modulating key pathways related to cellular development, inflammation, and metabolism.

Target Controllability: a Feed-Forward Greedy Algorithm in Complex Networks, Meeting Kalman's Rank Condition.

The concept of controllability within complex networks is pivotal in determining the minimal set of driver vertices required for the exertion of external signals, thereby enabling control over the entire network's vertices. Target controllability further refines this concept by focusing on a subset of vertices within the network as the specific targets for control, both of which are known to be NP-hard problems. Crucially, the effectiveness of the driver set in achieving control of the network is contingent upon satisfying a specific rank condition, as introduced by Kalman. On the other hand, structural controllability provides a complementary approach to understanding network control, emphasizing the identification of driver vertices based on the network's structural properties. However, in structural controllability approaches, the Kalman condition may not always be satisfied. In this study, we address the challenge of target controllability by proposing a feed-forward greedy algorithm designed to efficiently handle large networks while meeting the Kalman controllability rank condition. We further enhance our method's efficacy by integrating it with Barabasi et al.'s structural controllability approach. This integration allows for a more comprehensive control strategy, leveraging both the dynamical requirements specified by Kalman's rank condition and the structural properties of the network. Empirical evaluation across various network topologies demonstrates the superior performance of our algorithms compared to existing methods, consistently requiring fewer driver vertices for effective control. Additionally, our method's application to protein-protein interaction networks associated with breast cancer reveals potential drug repurposing candidates, underscoring its biomedical relevance. This study highlights the importance of addressing both structural and dynamical aspects of network controllability for advancing control strategies in complex systems. The source code is available for free at: Https://github.com/fatemeKhezry/targetControllability. Supplementary data are available at Bioinformatics online.

Uncovering seed vigor responsive miRNA in hybrid wheat and its parents by deep sequencing

BackgroundTwo-line hybrid wheat technology system is one way to harness wheat heterosis both domestically and internationally. Seed vigor is a crucial parameter for assessing seed quality, as enhanced seed vigor can lead to yield increments of over 20% to a certain extent. MicroRNAs (miRNAs) were known to participate in the development and vigor of seed in plants, but its impact on seed vigor in two-line hybrid wheat remains poorly elucidated.ResultsThe hybrid (BS1453/11GF5135) wheat exhibited superiority in seed vigor and anti-aging capacity, compared to its male parent (11GF5135, MP) and female parent (BS1453, FP). We identified four miRNAs associated with seed vigor, all of which are novel miRNAs. The majority of targets of miRNAs were related to ubiquitin ligases, kinases, sucrose synthases and hydrolases, involving in starch and sucrose metabolism, hydrolysis, catalysis, plant hormone signal transduction, and other pathways, which played crucial roles in seed development. Additionally, we also found miR531 was differentially expressed in both male parent and hybrid, and its target gene was a component of the E1 subunit of α-ketoate dehydrogenase complex, which interacted with dihydrolipoamide acetyltransferase (E2) and dihydrolipoyl dehydrogenase (E3). Finally, We established a presumptive interaction model to speculate the relationship of miR531 and seed vigor.ConclusionsThis study analyzed the seed vigor of two-line hybrid wheat, and screened seed vigor-related miRNAs. Meanwhile speculated the genetic relationship of hybrid and parents, in terms of miRNAs. Consequently, the present study provides new insights into the miRNA-mediated gene and protein interaction network that regulates seed vigor. These findings hold significance for enhancing the yield and quality of two-line hybrid wheat, facilitating its future applications.

Exploring the material basis and molecular targets of Changma Xifeng tablet in treating Tourette syndrome: an integrative approach of network pharmacology and miRNA analysis.

This study was to investigate the mechanism of Changma Xifeng tablet, a traditional Chinese medicine in the treatment of Tourette syndrome. Network pharmacology was utilized to pinpoint blood-entering constituents of Changma Xifeng and explore their potential targets. Additionally, differential microRNA expression analysis was conducted to predict Tourette syndrome-associated targets, complemented by molecular docking and dynamics simulations to support the interactions of the active compounds with these targets. The study identified 98 common targets between Changma Xifeng and Tourette syndrome, which may be involved in the treatment process. A protein-protein interaction network and a drug-active ingredient-disease target network highlighted the formulation's multi-component, multi-target therapeutic approach. Eight pivotal targets-AR, GRM5, MET, RORA, HTR2A, CNR1, PDE4B, and TOP1-were identified at the intersection of microRNA and drug targets. Molecular docking revealed 12 complexes with favorable binding energies below - 7kcal/mol, specifically: AR with Alfacalcidol, TOP1 with Albiflorin, GRM5 with Arachidic Acid, GRM5 with Palmitic Acid, AR with Arachidic Acid, AR with 2-Hydroxyoctadecanoic Acid, RORA with Pinellic Acid, RORA with Palmitic Acid, AR with Acoronene, AR with Epiacoronene, AR with 4,4'-Methylenediphenol, and HTR2A with Calycosin. Our molecular docking and molecular dynamics simulations suggest potential stable interactions between the formulation's active components and target proteins. These computational methods provide a preliminary theoretical framework that will guide our future experimental work. The study provides a scientific rationale for the use of traditional Chinese medicine in Tourette syndrome management and offers new insights for drug development.

Distinct deregulation trends of transcriptional protein complexes in aging naive T cells.

The impact of aging on T cell subsets, specifically CD4+ and CD8+ T cells, leading to immune system dysfunction, has been the focus of scientific investigation due to its potential to reverse age-associated deterioration. Transcriptomic and epigenomic studies have identified the primary regulators in T cell aging. However, comprehending the underlying dynamic mechanisms requires studying these proteins with their interactors. Here, we integrated single-cell RNA sequencing data of naive CD4+ and CD8+ T cells obtained from three different age groups with protein-protein and domain-domain interaction networks to predict and compare the transcriptional protein complexes and identify their capacity to explain age-associated variances. Our novel approach revealed significant effects of aging on the repertoire of complexes, which remains unchanged in naive CD4+ T cells, while in naive CD8+ T cells, it diminishes. In both cell types, there was major deregulation of complexes with the same composition, involving a range of transcription factors. This aging-associated deregulation is characterized by a specific set of protein complexes in naive CD4+ T cells, but this pattern is not observed in naive CD8+ T cells. SMAD3 and BCL11A complexes emerge as key markers in defining a trajectory in aging naive CD4+ T cells. These complexes can accurately distinguish between three different age groups, indicating their potential as targets. The direct link between SMAD3 and FOS complexes whose regulatory role has been previously implicated in aging and MBD3 as the novel key link between SMAD3 and BCL11A complexes implicate a coordinated mechanism in age-associated deregulation.

Identification of key signaling pathways and novel computational drug target for oral cancer, metabolic disorders and periodontal disease

AimDue to conventional endocrinological methods, there is presently no shared work available, and no therapeutic options have been demonstrated in oral cancer (OC) and periodontal disease (PD), type 2 diabetes (T2D), and obese patients. The aim of this study is to determine the similar molecular pathways and potential therapeutic targets in PD, OC, T2D, and obesity that may be used to anticipate the progression of the disease. MethodsFour Gene Expression Omnibus (GEO) microarray datasets (GSE29221, GSE15773, GSE16134, and GSE13601) are used for finding differentially expressed genes (DEGs) for T2D, obese, and PD patients with OC in order to explore comparable pathways and therapeutic medications. Gene ontology (GO) and pathway analysis were used to investigate the functional annotations of the genes. The hub genes were then identified using protein-protein interaction (PPI) networks, and the most significant PPI components were evaluated using a clustering approach. ResultsThese three gene expression-based datasets yielded a total of seven common DEGs. According to the GO annotation, the majority of the DEGs were connected with the microtubule cytoskeleton structure involved in mitosis. The KEGG pathways revealed that the concordant DEGs are connected to the cell cycle and progesterone-mediated oocyte maturation. Based on topological analysis of the PPI network, major hub genes (CCNB1, BUB1, TTK, PLAT, and AHNAK) and notable modules were revealed. This work additionally identified the connection of TF genes and miRNAs with common DEGs, as well as TF activity. ConclusionPredictive drug analysis yielded concordant drug compounds involved with T2D, OC, PD, and obesity disorder, which might be beneficial for examining the diagnosis, treatment, and prognosis of metabolic disorders and Oral cancer.