Growing Directed Acyclic Graphs: Optimization Functions for Pathway Reconstruction Algorithms.

BACKGROUNDStudies show that the antifibrotic mechanism of taurine may involve its inhibition of the activation and proliferation of hepatic stellate cells (HSCs). Since the molecular mechanism of taurine-mediated antifibrotic activity has not been fully unveiled and is little studied, it is imperative to use “omics” methods to systematically investigate the molecular mechanism by which taurine inhibits liver fibrosis.AIMTo establish a network including transcriptomic and protein-protein interaction data to elucidate the molecular mechanism of taurine-induced HSC apoptosis.METHODSWe used microarrays, bioinformatics, protein-protein interaction (PPI) network, and sub-modules to investigate taurine-induced changes in gene expression in human HSCs (LX-2). Subsequently, all of the differentially expressed genes (DEGs) were subjected to gene ontology function and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. Furthermore, the interactions of DEGs were explored in a human PPI network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software.RESULTSA total of 635 DEGs were identified in taurine-treated HSCs when compared with the controls. Of these, 304 genes were statistically significantly up-regulated, and 331 down-regulated. Most of these DEGs were mainly located on the membrane and extracellular region, and are involved in the biological processes of signal transduction, cell proliferation, positive regulation of extracellular regulated protein kinases 1 (ERK1) and ERK2 cascade, extrinsic apoptotic signaling pathway and so on. Fifteen significantly enriched pathways with DEGs were identified, including mitogen-activated protein kinase (MAPK) signaling pathway, peroxisome proliferators-activated receptor signaling pathway, estrogen signaling pathway, Th1 and Th2 cell differentiation, cyclic adenosine monophosphate signaling pathway and so on. By integrating the transcriptomics and human PPI data, nine critical genes, including MMP2, MMP9, MMP21, TIMP3, KLF10, CX3CR1, TGFB1, VEGFB, and EGF, were identified in the PPI network analysis.CONCLUSIONTaurine promotes the apoptosis of HSCs via up-regulating TGFB1 and then activating the p38 MAPK-JNK-Caspase9/8/3 pathway. These findings enhance the understanding of the molecular mechanism of taurine-induced HSC apoptosis and provide references for liver disorder therapy.

The purpose of the current study was to explore the carboplatin-induced sequential changes in gene expression and screen out key genes, which were associated with effects of carboplatin on epithelial ovarian cancer (EOC). The microarray dataset GSE13525 was downloaded from the Gene Expression Omnibus database, including 6 EOC cell samples separately treated with carboplatin at 24, 30 and 36 h (case group), and 6 samples treated with phosphate-buffered saline at the same time points (control group). A total of 3 sets of differentially expressed genes (DEGs) were respectively identified in case samples at 24, 30 and 36 h compared with the control group via the Limma package, and separately recorded as DEG-24, DEG-30 and DEG-36. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the overlapped DEGs were performed via the Database for Annotation, Visualization and Integrated Discovery. The protein-protein interaction (PPI) network was constructed and analyzed by Cytoscape software. In addition, the survival curves were drawn to illustrate the association between the expression levels of certain critical genes and the prognosis of EOC. A total of 170, 605 and 1043 DEGs were separately obtained in DEG-24 DEG-30 and DEG-36, and 110 overlaps were identified. The overlaps were enriched in 77 GO terms and 3 KEGG pathways. A total of 152 pairs were involved in the PPI network, and the abnormal expression levels (high or low) of c-Jun and cyclin B1 (CCNB1) would reduce the survival time of patients with EOC. The study indicated that c-Jun and CCNB1 may be the prognostic biomarkers of EOC treated with carboplatin, and certain pathways (such as p53 signaling pathway, cell cycle and mitogen-activation protein kinase signaling pathway) may be involved in carboplatin-resistant EOC.

Based on benchmarking various methods and analyzing multiple real scRNA-seq datasets, a computational platform/workflow and a set of tips for best practices are developed for analyzing causal interactions or relationships in single cells.

This study aims to utilize microarray data deposited by Romero et al. and conduct bioinformatic analysis for identifying differentially expressed genes (DEGs) associated with a novel method involving gene correction at the Alanine–Glyoxylate Aminotransferase (AGXT) locus and direct conversion of fibroblasts from primary hyperoxaluria type 1 (PH1) patients into healthy induced hepatocytes (iHeps) using Clustered Regularly Interspaced Short Palindromic Repeats - CRISPR-associated protein 9 (CRISPR-Cas9) technology. Additionally, the study aims to elucidate the molecular mechanisms underlying hyperoxaluria compared to oxalate crystal formation. Romero et al.'s GSE226019 microarray data was retrieved from Gene Expression Omnibus. Statistical analysis was done in R and Bioconductor, utilizing rigorous methods to ensure robust and reproducible results. The limma program compared gene expression levels across groups. Pathway analysis, protein-protein interaction (PPI) network creation, and miRNA-target interaction network analysis were constructed. The top ten DEGs included ANGPTL3, SLC38A3, KNG1, BDH1, GC, ADH1C, ARG1, CYP3A4, AMBP, and CYP2C9. Enrichment analysis revealed significant associations with various biological pathways, including Linoleic acid metabolism and Retinol metabolism. Volcano plots and mean difference plots highlighted significant gene expression changes between different sample groups. Protein-protein interaction networks and miRNA-target interaction networks provided insights into molecular interactions and regulatory mechanisms. The top ten differentially expressed genes include ANGPTL3, SLC38A3, KNG1, BDH1, GC, ADH1C, ARG1, CYP3A4, AMBP, and CYP2C9—emerge as key players with strong associations to critical biological pathways like Linoleic acid metabolism and drug metabolism-cytochrome P450. Understanding the regulatory role of specific miRNAs (hsa-miR-4501, hsa-miR-5692c, hsa-miR-6731-3p, hsa-miR-6867-5p, hsa-miR-616-3p, hsa-miR-4468, hsa-miR-3692-3p, hsa-miR-4277, hsa-miR-4763-5p, hsa-miR-4797-5p) in gene expression could provide further insights into disease mechanisms and potential therapeutic avenues. The statistical findings provide a foundation for predictive modeling, hypothesis testing, and exploring personalized therapeutic strategies.

Protein kinase C (PKC) isozymes are key signal transducers involved in normal physiology and disease and have been widely implicated in cancer progression. Despite our extensive knowledge of the signaling pathways regulated by PKC isozymes and their effectors, there is essentially no information on how individual members of the PKC family regulate gene transcription. Here, we report the first PKC isozyme-specific analysis of global gene expression by microarray using RNAi depletion of diacylglycerol/phorbol ester-regulated PKCs. A thorough analysis of this microarray data revealed unique patterns of gene expression controlled by PKCα, PKCδ, and PKCε, which are remarkably different in cells growing in serum or in response to phorbol ester stimulation. PKCδ is the most relevant isoform in controlling the induction of genes by phorbol ester stimulation, whereas PKCε predominantly regulates gene expression in serum. We also established that two PKCδ-regulated genes, FOSL1 and BCL2A1, mediate the apoptotic effect of phorbol esters or the chemotherapeutic agent etoposide in prostate cancer cells. Our studies offer a unique opportunity for establishing novel transcriptional effectors for PKC isozymes and may have significant functional and therapeutic implications.

Chapter 9 - Changes in cortical gene expression in major depressive disorders: More evidence implicating inflammatory-related pathways in disease etiology

Postmortem and neuroimaging studies show low levels of cortical muscarinic M1 receptors (CHRM1) in patients with schizophrenia which is significant because CHRM signalling has been shown to change levels of gene expression and cortical gene expression is altered in schizophrenia. We decided to identify CHRM1-mediated changes in cortical gene expression by measuring levels of RNA in the cortex of the Chrm1−/− mouse (n = 10), where there would be no signalling by that receptor, and in wild type mouse (n = 10) using the Affymetrix Mouse Exon 1.0 ST Array. We detected RNA for 15,501 annotated genes and noncoding RNA of which 1,467 RNAs were higher and 229 RNAs lower in the cortex of the Chrm1−/− mouse. Pathways and proteins affected by the changes in cortical gene expression in the Chrm1−/− are linked to the molecular pathology of schizophrenia. Our human cortical gene expression data showed 47 genes had altered expression in Chrm1−/− mouse and the frontal pole from patients with schizophrenia with the change in expression of 44 genes being in opposite directions. In addition, genes with altered levels of expression in the Chrm1−/− mouse have been shown to affect amyloid precursor protein processing which is associated with the pathophysiology of Alzheimer’s disease, and 69 genes with altered expression in the Chrm1−/− mouse are risk genes associated with human cognitive ability. Our findings argue CHRM1-mediated changes in gene expression are relevant to the pathophysiologies of schizophrenia and Alzheimer’s disease and the maintenance of cognitive ability in humans.

The Impact of Gene Expression Regulation on Evolution of Extracellular Signaling Pathways

Integrating rapid responses to 1,25-dihydroxyvitamin D 3 with transcriptional changes in osteoblasts: Ca 2+ regulated pathways to the nucleus

DOI: 10.1111/j.1474-9726.2009.00534.x After publication of Cao et al. (2010) the authors would like to include their microarray data as part of the Supporting Information for the article. The updated list of Supporting Information available for this article is as follows: Supporting Information Additional supporting information may be found in the online version of this article: Fig. S1 Hierarchical clustering heat map of gene expression changes associated with aging and GO biological processes. Fig. S2 Age-associated gene expression changes involved in T-cell signaling transduction pathways as generated by Ingenuity Pathway analysis. a, b, c, d, e, f, g, h: left panel, pathways with age-associated gene expression changes denoted by green, down-, and red, up-regulated genes (detailed gene information, supporting Table S5); right panel, heat maps of expression changes for component genes. I: symbol definitions. Table S1 A gene list of 754 genes (897 genes IDs, viz., some genes have more than two gene IDs) presenting expression changes associated with aged CD8+ T cells. Table S2-1 List of genes with significant monotonic age-associated expression changes from five young, two 65-year and two 80-year-old donor groups, with corresponding functional categories. Table S2-2 Pearson’s correlation analyses of genes within each biological process with monotonic age-associated expression changes. Table S3 A list of gene expression fold-changes as analyzed by microarray and qRT-PCR. Table S4 A list of age-associated gene expression changes involved in gene transcription processes. Table S5 A list of age-associated gene expression changes involved in signal transduction pathways. Table S6 Expression levels of all genes of each donor, as determined using HG-U133A_2 Gene Array chips and normalized by gc-RMA. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer-reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.

Ablative fractional laser treatment is considered the gold standard for skin rejuvenation. In order to understand how fractional laser works to rejuvenate skin, we performed microarray profiling on skin biopsies to identify temporal and dose-response changes in gene expression following fractional laser treatment. The backs of 14 women were treated with ablative fractional laser (Fraxel®) and 4 mm punch biopsies were collected from an untreated site and at the treated sites 1, 3, 7, 14, 21 and 28 days after the single treatment. In addition, in order to understand the effect that multiple fractional laser treatments have on skin rejuvenation, several sites were treated sequentially with either 1, 2, 3, or 4 treatments (with 28 days between treatments) followed by the collection of 4 mm punch biopsies. RNA was extracted from the biopsies, analyzed using Affymetrix U219 chips and gene expression was compared between untreated and treated sites. We observed dramatic changes in gene expression as early as 1 day after fractional laser treatment with changes remaining elevated even after 1 month. Analysis of individual genes demonstrated significant and time related changes in inflammatory, epidermal, and dermal genes, with dermal genes linked to extracellular matrix formation changing at later time points following fractional laser treatment. When comparing the age-related changes in skin gene expression to those induced by fractional laser, it was observed that fractional laser treatment reverses many of the changes in the aging gene expression. Finally, multiple fractional laser treatments, which cover different regions of a treatment area, resulted in a sustained or increased dermal remodeling response, with many genes either differentially regulated or continuously upregulated, supporting previous observations that maximal skin rejuvenation requires multiple fractional laser treatments. In conclusion, fractional laser treatment of human skin activates a number of biological processes involved in wound healing and tissue regeneration.

We intend to explore potential mechanisms of Tripterygium wilfordii Hook.f (TwHF) induced kidney injury (KI) using the methods of network toxicology and molecular docking. We determined TwHF potential compounds with its targets and KI targets, obtained the TwHF induced KI targets after intersecting targets of TwHF and KI. Then we conducted protein-protein interaction (PPI) network, gene expression analysis, gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis to explore the mechanism of TwHF-induced KI. Finally we conducted molecular docking to verify the core toxic compounds and the targets. We obtained 12 TwHF toxic compounds and 62 TwHF-induced KI targets. PPI network, gene expression analysis and GO function enrichment analysis unveiled the key biological process and suggested the mechanism of TwHF-induced KI might be associated with inflammation, immune response, hypoxia as well as oxidative stress. KEGG pathway enrichment analysis indicated PI3K-Akt signaling pathway, HIF-1 signaling pathway and TNF signaling pathway were key signaling pathways of TwHF induced KI. Molecular docking showed that the binding energy of core targets and toxic compounds was all less than -6.5 kcal/mol that verified the screening ability of network pharmacology and provided evidence for modifying TwHF toxic compounds structure. Through the study, we unveiled the mechanism of TwHF induce KI that TwHF might activate PI3K-Akt signaling pathway as well as TNF signaling pathway to progress renal inflammation, mediate hypoxia via HIF-1 signaling pathway to accelerate inflammatory processes, and also provided a theoretical basis for modifying TwHF toxic compounds structure as well as supported the follow-up research.

Glioblastoma (GBM) is the most aggressive and lethal tumor of the central nervous system. The present study set out to identify reliable prognostic and predictive biomarkers for patients with GBM. RNA-sequencing data were obtained from The Cancer Genome Atlas database and DNA methylation data were downloaded using the University of California Santa Cruz-Xena database. The expression and methylation differences between patients with GBM, and survival times <1 and ≥1 year were investigated. A protein-protein interaction network was constructed and functional enrichment analyses of differentially expressed and methylated genes were performed. Hub genes were identified using the Cytoscape plug-in cytoHubba software. Survival analysis was performed using the survminer package, in order to determine the prognostic values of the hub genes. The present study identified 71 genes that were hypomethylated and expressed at high levels, and four genes that were hypermethylated and expressed at low levels in GBM. These genes were predominantly enriched in the ‘JAK-STAT signaling pathway’, ‘transcriptional misregulation in cancer’ and the ‘ECM-receptor interaction’, which are associated with GBM development. Among the 24 hub genes identified, 15 possessed potential prognostic value. An integrative analysis approach was implemented in order to analyze the association of DNA methylation with changes in gene expression and to assess the association of gene expression changes with GBM survival time. The results of the present study suggest that these 15 CpG-based genes may be useful and practical tools in predicting the prognosis of patients with GBM. However, future research on gene methylation and/or expression is required in order to develop personalized treatments for patients with GBM.

To identify the repertoire of ephrin genes that might regulate endochondral bone fracture repair, we examined changes in ephrin ligand and receptor (Eph) gene expression in fracture callus tissues during bone fracture healing. Ephrin and Eph proteins were then localized in the fracture callus tissues present when changes in gene expression were observed. Ephrin gene expression was widespread in fracture tissues, but the repertoire of ephrin genes with significant changes in expression that might suggest a regulatory role in fracture callus development was restricted to the ephrin A family members Epha4, Epha5 and the ephrin B family member Efnb1. After 3 weeks of healing, Epha4 fracture expression was downregulated from 1.3- to 0.8-fold and Epha5 fracture expression was upregulated from 1.2- to 1.5-fold of intact contralateral femur expression, respectively. Efnb1 expression was downregulated from 1.5- to 1.2-fold after 2 weeks post-fracture. These ephrin proteins were localized to fracture callus prehypertrophic chondrocytes and osteoblasts, as well as to the periosteum and fibrous tissues. The observed positive correlation between mRNA levels of EfnB1 with Col10 and Epha5 with Bglap, together with colocalized expression with their respective proteins, suggest that EfnB1 is a positive mediator of prehypertrophic chondrocyte development and that Epha5 contributes to osteoblast-mediated mineralization of fracture callus. In contrast, mRNA levels of Epha4 and Efnb1 correlated negatively with Bglap, thus suggesting a negative role for these two ephrin family members in mature osteoblast functions. Given the number of family members and widespread expression of the ephrins, a characterization of changes in ephrin gene expression provides a basis for identifying ephrin family members that might regulate the molecular pathways of bone fracture repair. This approach suggests that a highly restricted repertoire of ephrins, EfnB1 and EphA5, are the major mediators of fracture callus cartilage hypertrophy and ossification, respectively, and proposes candidates for additional functional study and eventual therapeutic application.

BackgroundPrevious studies found that rats subjected to carrageenan injection develop hyperalgesia, and despite complete recovery in several days, they continue to have an enhanced hyperalgesic response to a new noxious challenge for more than 28d. The study's aim was to identify candidate genes that have a role in the formation of the long-term hyperalgesia-related imprint in the spinal cord. This objective was undertaken with the understanding that the long-lasting imprint of acute pain in the central nervous system may contribute to the transition of acute pain to chronicity.ResultsTo analyze changes in gene expression when carrageenan-induced hyperalgesia has disappeared but propensity for the enhanced hyperalgesic response is still present, we determined the gene expression profile using oligo microarray in the lumbar part of the spinal cord in three groups of rats: 28d after carrageenan injection, 24h after injection (the peak of inflammation), and with no injection (control group). Out of 17,000 annotated genes, 356 were found to be differentially expressed compared with the control group at 28d, and 329 at 24h after carrageenan injection (both groups at p < 0.01). Among differentially expressed genes, 67 (39 in 28d group) were identified as being part of pain-related pathways, altered in different models of pain, or interacting with proteins involved in pain-related pathways. Using gene ontology (GO) classification, we have identified 3 functional classes deserving attention for possible association with pain memory: They are related to cell-to-cell interaction, synaptogenesis, and neurogenesis.ConclusionDespite recovery from inflammatory hyperalgesia, persistent changes in spinal cord gene expression may underlie the propensity for the enhanced hyperalgesic response. We suggest that lasting changes in expression of genes involved in the formation of new synapses and neurogenesis may contribute to the transition of acute pain to chronicity.