Comparison of Two Experimental Mouse Dry Eye Models through Inflammatory Gene Set Enrichment Analysis Based on a Multiplexed Transcriptomic Approach.
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SUBMITTER: Kessal K
PROVIDER: S-EPMC8509332 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The aim of the present study was to investigate the anti-inflammatory effects of glycine thymosin ?4 (Gly-T?4) eye drops, and to compare the efficacy of topical Gly-T?4 with Cyclosporine A (CsA) in a mouse model of experimental dry eye (EDE). Eye drops consisting of balanced salt solution (BSS), 0.1% Gly-T?4 or 0.05% CsA were used for treatment of EDE. Tear volume, tear film break-up time and corneal staining scores were measured after 7 and 14 days. Periodic acid-Schiff staining for conjunctival gobleT cells, TUNEL assay for corneal apoptotic positive cells, multiplex immunobead assay for interleukin (IL)-1?, IL-6, tumor necrosis factor-? and interferon-? levels, and flow cytometry for CD4+/CCR5+ T cells were performed after 14 days. All clinical parameters showed improvement in the Gly-T?4 and CsA groups (all P<0.05). Significantly increased conjunctival gobleT cells and decreased corneal TUNEL positive cells were observed in the Gly-T?4 and CsA groups. The Gly-T?4 and CsA treated groups showed significantly reduced inflammatory cytokine levels and T cells in the conjunctiva compared with the EDE and BSS groups (all P<0.05). However, there were no significant differences observed in the inflammatory and clinical parameters between the Gly-T?4 and CsA treatment groups. Topical application of 0.1% Gly-T?4 significantly reduced inflammation on the ocular surface, as well as clinical parameters of EDE, with a similar efficacy to that of 0.05% CsA emulsions, suggesting that Gly-T?4 eye drops may be used as a therapeutic agent for treatment of dry eye disease.
| S-EPMC7201140 | biostudies-literature
Project description:The purpose of this study has been the investigation of the effect of novel peptide hydroxyproline-GQDGLAGPK (Hyp-GQDGLAGPK) in desiccation stress-induced dry eye mouse model and compared medicines for dry eye disease including cyclosporine, diquafosol and sodium hyaluronate. Seventy eight NOD.B10.H2 b mice were injected with scopolamine and exposed to an air draft for 10 days, and then the mice were treated with normal saline (n = 13), 1% Hyp-GQDGLAGPK (n = 13), 0.05% cyclosporine (n = 13), 3% diquafosol (n = 13), and 0.1% hyaluronate (n = 13) for 10 days. Thirteen mice were used for histopathologic analysis at DS 10d. The desiccation stress significantly decreased tear production, but the topical treatment of Hyp-GQDGLAGPK recovered to the baseline levels, which was similar to cyclosporine and diquafosol. In addition, Hyp-GQDGLAGPK improved facilitating epithelium stabilization including the corneal irregularity score, fluorescein score and detachment of the corneal epithelium. These improvements in stabilization of the corneal epithelium was superior to that in the cyclosporine and sodium hyaluronate groups. Furthermore, desiccation stress markedly induced expression of autoimmune inflammation-related factors in the lacrimal glands, but it was significantly suppressed by Hyp-GQDGLAGPK treatment. Overall, we found that novel peptide Hyp-GQDGLAGPK has multi-functional effects such as stabilizing the tear film and inhibiting inflammation.
| S-EPMC5547052 | biostudies-other
Project description:ObjectiveTo investigate the clinical effects of IRT5 probiotics in the environmental dry eye model.MethodsEight week old male C57BL/6 mice were randomly divided into two groups; control group (n = 16) received oral gavage of 300 μL phosphate-buffered saline (PBS) alone once daily, IRT5 group (n = 9) received oral gavage of 1 x 109 CFU IRT5 probiotics powder in 300 μL PBS once daily, both groups for 11 to 12 days. Simultaneously, all mice underwent dry eye induction. Tear secretion, corneal staining and conjunctival goblet cell density were evaluated. Quantative real-time polymerase chain reaction (RT-PCR) for inflammation-related markers was performed. 16S ribosomal RNA of fecal microbiome was analyzed and compositional difference, alpha and beta diversities were assessed.ResultsThere was no difference in NEI score but significant increase in tear secretion was observed in IRT5 group (p < 0.001). There was no significant difference in goblet cell density between groups. Quantative RT-PCR of cornea and conjunctiva revealed increased TNF-α expression in IRT5 group (p < 0.001) whereas other markers did not significantly differ from control. IRT5 group had significantly increased species diversity by Shannon index (p = 0.041). Beta diversity of genus by UniFrac principle coordinates analysis showed significant distance between groups (p = 0.001). Compositional differences between groups were observed and some were significantly associated with tear secretion. Multivariate linear regression analysis revealed Christensenellaceae (p = 0.009), Lactobacillus Helveticus group (p = 0.002) and PAC001797_s (p = 0.011) to strongly influence tear secretion.ConclusionIn experimental dry eye model, IRT5 probiotics treatment partially improves experimental dry eye by increasing tear secretion which was associated with and influenced by the change in intestinal microbiome. Also, intestinal microbiome may affect the lacrimal gland through a different mechanism other than regulating inflammation.
| S-EPMC7707591 | biostudies-literature
Project description:Dry eye disease (DED) is a complex multifactorial disease showing heterogenous symptoms, including dryness, photophobia, ocular discomfort, irritation and burning but also pain. These symptoms can affect visual function leading to restrictions in daily life activities and reduction in work productivity with a consequently high impact on quality of life. Several pathological mechanisms contribute to the disease: evaporative water loss leads to impairment and loss of tear homeostasis inducing either directly or indirectly to inflammation, in a self-perpetuating vicious cycle. Dysregulated ocular immune responses result in ocular surface damage, which further contributes to DED pathogenesis. Currently, DED treatment is based on a flexible stepwise approach to identify the most beneficial intervention. Although most of the available treatments may control to a certain extent some signs and symptoms of DED, they show significant limitations and do not completely address the needs of patients suffering from DED. This review provides an overview of the emerging experimental therapies for DED. Several promising therapeutic strategies are under development with the aim of dampening inflammation and restoring the homeostasis of the ocular surface microenvironment. Results from early phase clinical trials, testing the effects of EnaC blockers, TRPM8 agonist or mesenchymal stem cells in DED patients, are especially awaited to demonstrate their therapeutic value for the treatment of DED. Moreover, the most advanced experimental strategies in the pipeline for DED, tivanisiran, IL-1R antagonist EBI-005 and SkQ1, are being tested in Phase III clinical trials, still ongoing. Nevertheless, although promising results, further studies are still needed to confirm efficacy and safety of the new emerging therapies for DED.
| S-EPMC8001578 | biostudies-literature
Project description:PurposeTo investigate the impact of transmembrane protein CMTM6 on the pathogenesis of dry eye disease (DED) and elucidate its potential mechanisms.MethodsCMTM6 expression was confirmed by database analysis, real-time polymerase chain reaction (RT-PCR), western blot, and immunohistochemistry. Tear secretion was measured using the phenol red thread test. Immune cell infiltration was assessed through flow cytometry. Barrier function was evaluated by fluorescein sodium staining, immunofluorescence staining of zonula occludens 1 (ZO-1), and electric cell-substrate impedance sensing (ECIS) assessment. For silencing CMTM6 expression, siRNA and shRNA were employed, along with lentiviral vector-mediated overexpression of CMTM6. Proinflammatory cytokine levels were analyzed by RT-PCR and cytometric bead array (CBA) analysis.ResultsCMTM6 showed high expression in healthy human and mouse corneal and conjunctival epithelium but was notably reduced in DED. Notably, this downregulation was correlated with disease severity. Cmtm6-/- dry eye (DE) mice displayed reduced tear secretion, severe corneal epithelial defects, decreased conjunctival goblet cell density, and upregulated inflammatory response. Additionally, Cmtm6-/- DE mice and CMTM6 knockdown human corneal epithelial cell-transformed (HCE-T) cells showed more severe barrier disruption and reduced expression of ZO-1. Knockdown of CMTM6 in HCE-T cells increased inflammatory responses induced by hyperosmotic stress, which was significantly mitigated by CMTM6 overexpression. Moreover, the level of phospho-p65 in hyperosmolarity-stimulated HCE-T cells increased after silencing CMTM6. Nuclear factor kappa B (NF-κB) p65 inhibition (JSH-23) reversed the excessive inflammatory responses caused by hyperosmolarity in CMTM6 knockdown HCE-T cells.ConclusionsThe reduction in CMTM6 expression on the ocular surface contributes to the pathogenesis of DED. The CMTM6-NF-κB p65 signaling pathway may serve as a promising therapeutic target for DED.
| S-EPMC10768713 | biostudies-literature
Project description:BackgroundTo investigate the anti-inflammatory and antioxidative effects of gallic acid (GA) on human corneal epithelial cells (HCECs) and RAW264.7 macrophages as well as its therapeutic effects in an experimental dry eye (EDE) mouse model.MethodsA cell counting kit-8 (CCK-8) assay was used to test the cytotoxicity of GA. The effect of GA on cell migration was evaluated using a scratch wound healing assay. The anti-inflammatory and antioxidative effects of GA in vitro were tested using a hypertonic model (HCECs) and an inflammatory model (RAW264.7 cells). The in vivo biocompatibility of GA was detected by irritation tests in rabbits, whereas the preventive and therapeutic effect of GA in vivo was evaluated using a mouse model of EDE.ResultsIn the range of 0-100 μM, GA showed no cytotoxicity in RAW264.7 cells or HCECs and did not delay the HCECs monolayer wound healing within 24 h. Ocular tolerance to GA in the in vivo irritation test was good after seven days. In terms of antioxidative activity, GA significantly reduced the intracellular reactive oxygen species (ROS) in lipopolysaccharide (LPS) activated RAW264.7 macrophages and HCECs exposed to hyperosmotic stress. Furthermore, after pre-treatment with GA, the expression levels of nuclear factor E2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), and NADPH quinone oxidoreductase-1 (NQO-1) were significantly upregulated in RAW264.7 macrophages. GA also exhibits excellent anti-inflammatory properties. This is mainly demonstrated by the ability of GA to effectively downregulate the nuclear transcription factor-κB (NF-κB) pathway in LPS-activated RAW264.7 macrophages and to reduce inflammatory factors, such as nitric oxide (NO), interleukin 6 (IL-6), and tumor necrosis factor alpha (TNF-α). In vivo efficacy testing results in a mouse model of EDE showed that GA can effectively prevent and inhibit the apoptosis of corneal epithelial cells (CECs), reduce inflammatory factors in the cornea and conjunctiva as well as protect goblet cells.ConclusionIn vitro and in vivo results indicate that GA possesses potent anti-inflammatory and antioxidative properties with no apparent cytotoxicity within the range of 0-100 μM. It is a promising eye drop formulation for the effective prevention and treatment of dry eye disease (DED).
| S-EPMC10150500 | biostudies-literature
Project description:MotivationGene-set enrichment analysis (GSEA) can be greatly enhanced by linear model (regression) diagnostic techniques. Diagnostics can be used to identify outlying or influential samples, and also to evaluate model fit and explore model expansion.ResultsWe demonstrate this methodology on an adult acute lymphoblastic leukemia (ALL) dataset, using GSEA based on chromosome-band mapping of genes. Individual residuals, grouped or aggregated by chromosomal loci, indicate problematic samples and potential data-entry errors, and help identify hyperdiploidy as a factor playing a key role in expression for this dataset. Subsequent analysis pinpoints suspected DNA copy number abnormalities of specific samples and chromosomes (most prevalent are chromosomes X, 21 and 14), and also reveals significant expression differences between the hyperdiploid and diploid groups on other chromosomes (most prominently 19, 22, 3 and 13)--differences which are apparently not associated with copy number.AvailabilitySoftware for the statistical tools demonstrated in this article is available as Bioconductor package GSEAlm.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC2579710 | biostudies-literature
Project description:MotivationGene set enrichment (GSE) analysis allows for an interpretation of gene expression through pre-defined gene set databases and is a critical step in understanding different phenotypes. With the rapid development of single-cell RNA sequencing (scRNA-seq) technology, GSE analysis can be performed on fine-grained gene expression data to gain a nuanced understanding of phenotypes of interest. However, with the cellular heterogeneity in single-cell gene profiles, current statistical GSE analysis methods sometimes fail to identify enriched gene sets. Meanwhile, deep learning has gained traction in applications like clustering and trajectory inference in single-cell studies due to its prowess in capturing complex data patterns. However, its use in GSE analysis remains limited, due to interpretability challenges.ResultsIn this paper, we present DeepGSEA, an explainable deep gene set enrichment analysis approach which leverages the expressiveness of interpretable, prototype-based neural networks to provide an in-depth analysis of GSE. DeepGSEA learns the ability to capture GSE information through our designed classification tasks, and significance tests can be performed on each gene set, enabling the identification of enriched sets. The underlying distribution of a gene set learned by DeepGSEA can be explicitly visualized using the encoded cell and cellular prototype embeddings. We demonstrate the performance of DeepGSEA over commonly used GSE analysis methods by examining their sensitivity and specificity with four simulation studies. In addition, we test our model on three real scRNA-seq datasets and illustrate the interpretability of DeepGSEA by showing how its results can be explained.Availability and implementationhttps://github.com/Teddy-XiongGZ/DeepGSEA.
| S-EPMC11236288 | biostudies-literature
Project description:The myriad of available hepatocyte in vitro models provides researchers the possibility to select hepatocyte-like cells (HLCs) for specific research goals. However, direct comparison of hepatocyte models is currently challenging. We systematically searched the literature and compared different HLCs, but reported functions were limited to a small subset of hepatic functions. To enable a more comprehensive comparison, we developed an algorithm to compare transcriptomic data across studies that tested HLCs derived from hepatocytes, biliary cells, fibroblasts, and pluripotent stem cells, alongside primary human hepatocytes (PHHs). This revealed that no HLC covered the complete hepatic transcriptome, highlighting the importance of HLC selection. HLCs derived from hepatocytes had the highest transcriptional resemblance to PHHs regardless of the protocol, whereas the quality of fibroblasts and PSC derived HLCs varied depending on the protocol used. Finally, we developed and validated a web application (HLCompR) enabling comparison for specific pathways and addition of new HLCs. In conclusion, our comprehensive transcriptomic comparison of HLCs allows selection of HLCs for specific research questions and can guide improvements in culturing conditions.
| S-EPMC9568534 | biostudies-literature
Project description:Recently, microarray data analyses using functional pathway information, e.g., gene set enrichment analysis (GSEA) and significance analysis of function and expression (SAFE), have gained recognition as a way to identify biological pathways/processes associated with a phenotypic endpoint. In these analyses, a local statistic is used to assess the association between the expression level of a gene and the value of a phenotypic endpoint. Then these gene-specific local statistics are combined to evaluate association for pre-selected sets of genes. Commonly used local statistics include t-statistics for binary phenotypes and correlation coefficients that assume a linear or monotone relationship between a continuous phenotype and gene expression level. Methods applicable to continuous non-monotone relationships are needed. Furthermore, for multiple experimental categories, methods that combine multiple GSEA/SAFE analyses are needed.For continuous or ordinal phenotypic outcome, we propose to use as the local statistic the coefficient of multiple determination (i.e., the square of multiple correlation coefficient) R2 from fitting natural cubic spline models to the phenotype-expression relationship. Next, we incorporate this association measure into the GSEA/SAFE framework to identify significant gene sets. Unsigned local statistics, signed global statistics and one-sided p-values are used to reflect our inferential interest. Furthermore, we describe a procedure for inference across multiple GSEA/SAFE analyses. We illustrate our approach using gene expression and liver injury data from liver and blood samples from rats treated with eight hepatotoxicants under multiple time and dose combinations. We set out to identify biological pathways/processes associated with liver injury as manifested by increased blood levels of alanine transaminase in common for most of the eight compounds. Potential statistical dependency resulting from the experimental design is addressed in permutation based hypothesis testing.The proposed framework captures both linear and non-linear association between gene expression level and a phenotypic endpoint and thus can be viewed as extending the current GSEA/SAFE methodology. The framework for combining results from multiple GSEA/SAFE analyses is flexible to address practical inference interests. Our methods can be applied to microarray data with continuous phenotypes with multi-level design or the meta-analysis of multiple microarray data sets.
| S-EPMC2636811 | biostudies-other