A modular cell-type focused inflammatory process network model for non-diseased pulmonary tissue.
Ontology highlight
ABSTRACT:
SUBMITTER: Westra JW
PROVIDER: S-EPMC3700945 | biostudies-literature | 2013
REPOSITORIES: biostudies-literature
Publications
A modular cell-type focused inflammatory process network model for non-diseased pulmonary tissue.
Westra Jurjen W JW Schlage Walter K WK Hengstermann Arnd A Gebel Stephan S Mathis Carole C Thomson Ty T Wong Ben B Hoang Vy V Veljkovic Emilija E Peck Michael M Lichtner Rosemarie B RB Weisensee Dirk D Talikka Marja M Deehan Renee R Hoeng Julia J Peitsch Manuel C MC
Bioinformatics and biology insights 20130620
Exposure to environmental stressors such as cigarette smoke (CS) elicits a variety of biological responses in humans, including the induction of inflammatory responses. These responses are especially pronounced in the lung, where pulmonary cells sit at the interface between the body's internal and external environments. We combined a literature survey with a computational analysis of multiple transcriptomic data sets to construct a computable causal network model (the Inflammatory Process Networ ...[more]
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Project description:BackgroundHumans and other organisms are equipped with a set of responses that can prevent damage from exposure to a multitude of endogenous and environmental stressors. If these stress responses are overwhelmed, this can result in pathogenesis of diseases, which is reflected by an increased development of, e.g., pulmonary and cardiac diseases in humans exposed to chronic levels of environmental stress, including inhaled cigarette smoke (CS). Systems biology data sets (e.g., transcriptomics, phosphoproteomics, metabolomics) could enable comprehensive investigation of the biological impact of these stressors. However, detailed mechanistic networks are needed to determine which specific pathways are activated in response to different stressors and to drive the qualitative and eventually quantitative assessment of these data. A current limiting step in this process is the availability of detailed mechanistic networks that can be used as an analytical substrate.ResultsWe have built a detailed network model that captures the biology underlying the physiological cellular response to endogenous and exogenous stressors in non-diseased mammalian pulmonary and cardiovascular cells. The contents of the network model reflect several diverse areas of signaling, including oxidative stress, hypoxia, shear stress, endoplasmic reticulum stress, and xenobiotic stress, that are elicited in response to common pulmonary and cardiovascular stressors. We then tested the ability of the network model to identify the mechanisms that are activated in response to CS, a broad inducer of cellular stress. Using transcriptomic data from the lungs of mice exposed to CS, the network model identified a robust increase in the oxidative stress response, largely mediated by the anti-oxidant NRF2 pathways, consistent with previous reports on the impact of CS exposure in the mammalian lung.ConclusionsThe results presented here describe the construction of a cellular stress network model and its application towards the analysis of environmental stress using transcriptomic data. The proof-of-principle analysis described here, coupled with the future development of additional network models covering distinct areas of biology, will help to further clarify the integrated biological responses elicited by complex environmental stressors such as CS, in pulmonary and cardiovascular cells.
| S-EPMC3224482 | biostudies-literature
Project description:BackgroundCritical to advancing the systems-level evaluation of complex biological processes is the development of comprehensive networks and computational methods to apply to the analysis of systems biology data (transcriptomics, proteomics/phosphoproteomics, metabolomics, etc.). Ideally, these networks will be specifically designed to capture the normal, non-diseased biology of the tissue or cell types under investigation, and can be used with experimentally generated systems biology data to assess the biological impact of perturbations like xenobiotics and other cellular stresses. Lung cell proliferation is a key biological process to capture in such a network model, given the pivotal role that proliferation plays in lung diseases including cancer, chronic obstructive pulmonary disease (COPD), and fibrosis. Unfortunately, no such network has been available prior to this work.ResultsTo further a systems-level assessment of the biological impact of perturbations on non-diseased mammalian lung cells, we constructed a lung-focused network for cell proliferation. The network encompasses diverse biological areas that lead to the regulation of normal lung cell proliferation (Cell Cycle, Growth Factors, Cell Interaction, Intra- and Extracellular Signaling, and Epigenetics), and contains a total of 848 nodes (biological entities) and 1597 edges (relationships between biological entities). The network was verified using four published gene expression profiling data sets associated with measured cell proliferation endpoints in lung and lung-related cell types. Predicted changes in the activity of core machinery involved in cell cycle regulation (RB1, CDKN1A, and MYC/MYCN) are statistically supported across multiple data sets, underscoring the general applicability of this approach for a network-wide biological impact assessment using systems biology data.ConclusionsTo the best of our knowledge, this lung-focused Cell Proliferation Network provides the most comprehensive connectivity map in existence of the molecular mechanisms regulating cell proliferation in the lung. The network is based on fully referenced causal relationships obtained from extensive evaluation of the literature. The computable structure of the network enables its application to the qualitative and quantitative evaluation of cell proliferation using systems biology data sets. The network is available for public use.
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Project description:Bradykinin, a member of the kallikrein-kinin system (KKS), is associated with an inflammatory response pathway with diverse vascular permeability functions, including thrombosis and blood coagulation. In majority, bradykinin signals through Bradykinin Receptor B2 (B2R). B2R is a G protein-coupled receptor (GPCR) coupled to G protein family such as Gαqs, Gαq/Gα11, Gαi1, and Gβ1γ2. B2R stimulation leads to the activation of a signaling cascade of downstream molecules such as phospholipases, protein kinase C, Ras/Raf-1/MAPK, and PI3K/AKT and secondary messengers such as inositol-1,4,5-trisphosphate, diacylglycerol and Ca2+ ions. These secondary messengers modulate the production of nitric oxide or prostaglandins. Bradykinin-mediated signaling is implicated in inflammation, chronic pain, vasculopathy, neuropathy, obesity, diabetes, and cancer. Despite the biomedical importance of bradykinin, a resource of bradykinin-mediated signaling pathway is currently not available. Here, we developed a pathway resource of signaling events mediated by bradykinin. By employing data mining strategies in the published literature, we describe an integrated pathway reaction map of bradykinin consisting of 233 reactions. Bradykinin signaling pathway events included 25 enzyme catalysis reactions, 12 translocations, 83 activation/inhibition reactions, 11 molecular associations, 45 protein expression and 57 gene regulation events. The pathway map is made publicly available on the WikiPathways Database with the ID URL: https://www.wikipathways.org/index.php/Pathway:WP5132 . The bradykinin-mediated signaling pathway map will facilitate the identification of novel candidates as therapeutic targets for diseases associated with dysregulated bradykinin signaling.
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Project description:It is well known that isolation and cultivation of primary hepatocytes cause major gene expression alterations. In the present genome-wide, time-resolved study of cultivated human and mouse hepatocytes, we made the observation that expression changes in culture strongly resemble alterations in liver diseases. Hepatocytes of both species were cultivated in collagen sandwich and in monolayer conditions. Genome-wide data were also obtained from human NAFLD, cirrhosis, HCC and hepatitis B virus-infected tissue as well as mouse livers after partial hepatectomy, CCl4 intoxication, obesity, HCC and LPS. A strong similarity between cultivation and disease-induced expression alterations was observed. For example, expression changes in hepatocytes induced by 1-day cultivation and 1-day CCl4 exposure in vivo correlated with R = 0.615 (p < 0.001). Interspecies comparison identified predominantly similar responses in human and mouse hepatocytes but also a set of genes that responded differently. Unsupervised clustering of altered genes identified three main clusters: (1) downregulated genes corresponding to mature liver functions, (2) upregulation of an inflammation/RNA processing cluster and (3) upregulated migration/cell cycle-associated genes. Gene regulatory network analysis highlights overrepresented and deregulated HNF4 and CAR (Cluster 1), Krüppel-like factors MafF and ELK1 (Cluster 2) as well as ETF (Cluster 3) among the interspecies conserved key regulators of expression changes. Interventions ameliorating but not abrogating cultivation-induced responses include removal of non-parenchymal cells, generation of the hepatocytes' own matrix in spheroids, supplementation with bile salts and siRNA-mediated suppression of key transcription factors. In conclusion, this study shows that gene regulatory network alterations of cultivated hepatocytes resemble those of inflammatory liver diseases and should therefore be considered and exploited as disease models.
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Project description:Here we demonstrate a technique to generate proteomic signatures of specific cell types within heterogeneous populations. While our method is broadly applicable across biological systems, we have limited the current work to study neural cell types isolated from human, post-mortem Alzheimer's disease (AD) and aged-matched non-symptomatic (NS) brains. Motivating the need for this tool, we conducted an initial meta-analysis of current, human AD proteomics studies. While the results broadly corroborated major neurodegenerative disease hypotheses, cell type-specific predictions were limited. By adapting our Formaldehyde-fixed Intracellular Target-Sorted Antigen Retrieval (FITSAR) method for proteomics and applying this technique to characterize AD and NS brains, we generated enriched neuron and astrocyte proteomic profiles for a sample set of donors (available at www.fitsarpro.appspot.com ). Results showed the feasibility for using FITSAR to evaluate cell-type specific hypotheses. Our overall methodological approach provides an accessible platform to determine protein presence in specific cell types and emphasizes the need for protein-compatible techniques to resolve systems complicated by cellular heterogeneity.
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Project description:BackgroundThe development of complex diseases is contributed by the combination of multiple factors and complicated interactions between them. Inflammation has recently been associated with many complex diseases and may cause long-term damage to the human body. In this study, we examined whether two types of complex disease, cerebrovascular disease (CVD) or major depression (MD), systematically altered the transcriptomes of non-diseased human tissues and whether inflammation is linked to identifiable molecular signatures, using post-mortem samples from the Genotype-Tissue Expression (GTEx) project.ResultsFollowing a series of differential expression analyses, dozens to hundreds of differentially expressed genes (DEGs) were identified in multiple tissues between subjects with and without a history of CVD or MD. DEGs from these disease-associated tissues-the visceral adipose, tibial artery, caudate, and spinal cord for CVD; and the hypothalamus, putamen, and spinal cord for MD-were further analyzed for functional enrichment. Many pathways associated with immunological events were enriched in the upregulated DEGs of the CVD-associated tissues, as were the neurological and metabolic pathways in DEGs of the MD-associated tissues. Eight gene-tissue pairs were found to overlap with those prioritized by our transcriptome-wide association studies, indicating a potential genetic effect on gene expression for circulating cytokine phenotypes.ConclusionCerebrovascular disease and major depression cause detectable changes in the gene expression of non-diseased tissues, suggesting that a possible long-term impact of diseases, lifestyles and environmental factors may together contribute to the appearance of "transcriptomic scars" on the human body. Furthermore, inflammation is probably one of the systemic and long-lasting effects of cerebrovascular events.
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2017-06-20 | GSE88883 | GEO
Project description:Pulmonary fibrosis is a complex pathological process characterized by massive destruction of the structure of lung tissues and aggravated pulmonary function impairment. The underlying mechanisms of pulmonary fibrosis are incompletely understood and therefore limited treatment options are available currently. Here, we report that MLN4924, an NEDD8 activation enzyme (NAE) activity-inhibiting molecule, blocks the maintenance and progression of established pulmonary fibrosis. We found that MLN4924 acts against bleomycin-induced pulmonary fibrosis mainly at the early inflammatory stage. Pharmacologically targeting the neddylation of Cullin-Ring E3 ligase (CRL) by MLN4924, significantly abrogated NF-κB responses, suppressed MAPK activity, and reduced secretion of TNF-α-elicited pro-inflammatory cytokines and MCP1-induced chemokines. MLN4924 inhibited pro-inflammatory responses while maintaining or increasing the production of the anti-inflammatory mediators such as anti-inflammatory interleukins (ILs) following bleomycin administration, which is closely correlated to its blocking NF-κB-mediated signaling. Consistently, our studies identified MLN4924 as a promising therapeutic drug for pulmonary fibrosis and suggested a potential role of MLN4924 that fine tunes the MAPK signaling pathway controlling the inflammatory reactions at the early stages of pulmonary fibrosis. In addition, our findings may broaden the potential practical application of MLN4924 as an effective therapeutic strategy against other inflammation-associated diseases.
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