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Adapted Boolean Network Models for Extracellular Matrix Formation

ABSTRACT: Background Rheumatoid arthritis (RA) is a chronic inflammatory disease, characterized by joint destruction and perpetuated by the synovial membrane (SM). In the inflamed SM, activated synovial fibroblasts (SFB) form the major cell type promoting development and progression of the disease by an abnormal expression/secretion of pro-inflammatory cytokines, tissue-degrading enzymes resulting in a predominant degradation of the extra-cellular matrix (ECM), and collagens causing joint fibrosis. We developed a new procedure, based on human knowledge and formal concept analysis (FCA), to simulate and analyze the temporal behaviour of regulatory and signaling networks. It was applied to a regulatory network (containing 18 genes from 5 functional groups) representing ECM formation and destruction in TGFβ - and TNFα -stimulated SFB. Results For the modelling of SFB-controlled ECM turnover in rheumatic diseases, Boolean network architecture was used as well as extensive literature information and revision by experimental gene expression data from stimulated SFB. In course of revision, the additional experimental information resulted in different biologically reasonable changes, yielding two Boolean networks that describe TGFβ and TNFα effects, respectively. The final simulations were further analyzed by the attribute exploration algorithm of FCA, integrating again the observed time series in a more fine-grained and automated manner. The generated temporal rules clearly reveal subtle regulatory relationships between different genes, co-expression patterns and converse gene expression regulation in rheumatic diseases. Conclusion The developed Boolean network based method for the dynamical analysis of regulatory and signaling networks represents a reliable systems biological solution for the improved understanding of complex regulatory pathways and the interactions among different genes in disease. The resulting knowledge base can be used for further analysis of the ECM system in human fibroblasts and may be queried to predict the functional consequences of observed (e.g. in diseases as RA) or hypothetical (e.g. for therapeutic purposes) gene expression disturbances.

ORGANISM(S): Homo sapiens

PROVIDER: GSE13837 | GEO | 2009/07/20

SECONDARY ACCESSION(S): PRJNA110515

REPOSITORIES: GEO

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Project description:Background ; Rheumatoid arthritis (RA) is a chronic inflammatory disease, characterized by joint destruction and perpetuated by the synovial membrane (SM). In the inflamed SM, activated synovial fibroblasts (SFB) form the major cell type promoting development and progression of the disease by an abnormal expression/secretion of pro-inflammatory cytokines, tissue-degrading enzymes resulting in a predominant degradation of the extra-cellular matrix (ECM), and collagens causing joint fibrosis. We developed a new procedure, based on human knowledge and formal concept analysis (FCA), to simulate and analyze the temporal behaviour of regulatory and signaling networks. It was applied to a regulatory network (containing 18 genes from 5 functional groups) representing ECM formation and destruction in TGFÎ² - and TNFÎ± -stimulated SFB. Results ; For the modelling of SFB-controlled ECM turnover in rheumatic diseases, Boolean network architecture was used as well as extensive literature information and revision by experimental gene expression data from stimulated SFB. In course of revision, the additional experimental information resulted in different biologically reasonable changes, yielding two Boolean networks that describe TGFÎ² and TNFÎ± effects, respectively. The final simulations were further analyzed by the attribute exploration algorithm of FCA, integrating again the observed time series in a more fine-grained and automated manner. The generated temporal rules clearly reveal subtle regulatory relationships between different genes, co-expression patterns and converse gene expression regulation in rheumatic diseases. Conclusion ; The developed Boolean network based method for the dynamical analysis of regulatory and signaling networks represents a reliable systems biological solution for the improved understanding of complex regulatory pathways and the interactions among different genes in disease. The resulting knowledge base can be used for further analysis of the ECM system in human fibroblasts and may be queried to predict the functional consequences of observed (e.g. in diseases as RA) or hypothetical (e.g. for therapeutic purposes) gene expression disturbances. Experiment Overall Design: Patients and tissue samples: Experiment Overall Design: Synovial membrane samples were obtained within 10 min following tissue excision upon joint replacement/synovectomy from RA and OA patients (n = 3 each). After removal, tissue samples were frozen and stored at -70Â°C. Informed patient consent was acquired and the study was approved by the ethics committees of the respective universities. RA patients were classified according to the American College of Rheumatology (ACR) criteria, OA patients according to the respective criteria for osteoarthritis. The preparation of primary semi-transformed synovial fibroblasts from RA and OA patients was performed as previously described (Zimmermann et al., Arthritis Res. 2001;3(1):72-6). Briefly, the tissue samples were minced and digested with trypsin/collagenase P. The resulting single cell suspension was cultured for seven days. Non-adherent cells were removed by medium exchange. SFB were then negatively purified using DynabeadsÂ® M 450 CD14 and subsequently cultured over 4 passages in DMEM containing 100 Î¼g/ml gentamycin, 100 Î¼g/ml penicillin/streptomycin, 20 mM HEPES, and 10% FCS. Experiment Overall Design: Cell stimulation and isolation of total RNA : Experiment Overall Design: At the end of the fourth passage, the SFB were stimulated by 10 ng/ml TGFÎ² or TNFÎ± in serum-free DMEM for 0, 1, 2, 4, and 12 h. At the end of each time point, medium was removed and the cells were digested with trypsin/versene (0.25%). Following centrifugation and washing with PBS, the cells were lysed with RLT buffer (Qiagen) and frozen at 70Â°C. Total RNA was isolated using the RNeasy Kit (Qiagen) according to the supplier's recommendation. Experiment Overall Design: Microarray data analysis: Experiment Overall Design: RNA probes were labelled according to the supplier's instructions (AffymetrixÂ®, Santa Clara, CA, USA). Analysis of gene expression was performed using U133 Plus 2.0 RNA microarrays. Hybridization and washing was performed according to the supplier's instructions. Microarrays were analyzed by laser scanning (Hewlett-Packard Gene Scanner). Background-corrected signal intensities were determined using the MAS 5.0 software (AffymetrixÂ®) and normalized among arrays to facilitate comparisons between different patients. For this purpose, arrays were grouped according to patient class the respective stimulus (TGFÎ² and TNFÎ±, n=6 each). The arrays in each group were normalized using quantile normalization. Experiment Overall Design: See publication for further details.

Project description:Rheumatoid synoviocytes, which consist of fibroblast-like synoviocytes (FLS) and synovial macrophages (SM), are crucial for the progression of rheumatoid arthritis (RA). Particularly, FLS of RA patients (RA-FLS) exhibit invasive characteristics reminiscent of cancer cells, destroying cartilage and bone, although it remains unresolved how RA-FLS exhibit invasive phenotype. RA-FLS and SM originate differently from mesenchymal and myeloid cells, respectively, but share many pathologic functions. However, the molecular signatures and biological networks representing the distinct and shared features of the two cell types are unknown. Presently, we performed global transcriptome profiling of FLS and SM obtained from RA and osteoarthritis patients. By comparing the transcriptomes, we identified distinct molecular signatures and cellular processes defining invasiveness of RA-FLS and pro-inflammatory properties of RA synovial macrophages (RA-SM), respectively. Interestingly, under interleukin1β-stimulated condition, RA-FLS newly acquired pro-inflammatory signature mimicking RA-SM without losing invasive properties. We next reconstructed a network model that delineates the shared, RA-FLS-dominant (invasive), and RA-SM-dominant (inflammatory) processes. From the network model, we selected 13 genes, including POSTN and TWIST1, as novel regulator candidates responsible for FLS invasiveness. Of note, POSTN and TWIST1 expressions were elevated in independent RA-FLS and were further instigated by interleukin1β. In vitro functional assays demonstrated the requirement of POSTN and TWIST1 for migration and invasion of RA-FLS stimulated with interleukin1β. Taken together, our systems approach to rheumatoid synovitis provides a basis for identifying novel regulators responsible for pathological features of RA-FLS and RA-SM, demonstrating how a certain type of cells acquires functional redundancy under chronic inflammatory conditions. To identify molecular signatures of FLS and MLS in RA joints, we isolated FLS from synovial tissues of RA and osteoarthritis (OA) patients, obtained synovial macrophages from synovial fluid of RA patients, and differentiated control macrophages from peripheral blood of healthy subjects. Also, we stimulated FLS with IL1β, and then analyzed gene expression profiles of both IL1β-stimulated RA-FLS and OA-FLS

Project description:Ectopic calcification in synovial tissues is devastating to diarthrodial joints. While some forms of synovial ectopic calcification have genetically simple basis, most cases manifest as complex traits with environmental and multigenic components. The location of causal loci or the physiological processes affected by allelic variants is poorly understood. Here, we report on genetic susceptibility to ectopic calcification in the LG/J and SM/J advanced intercross mice. Using 347 mice in 98 full-sibships, destabilization of medial meniscus was performed to induce joint injury. We performed quantitative trait locus (QTL) analysis to map calcification phenotypes to discrete genomic locations. To validate the functional significance of the selected QTL candidate genes, we compared mRNA expression between parental LG/J and SM/J inbred strains. Our findings showed that joint destabilization instigated ectopic calcifications as detected and quantified by micro-CT. Overall, we detected 20 QTLs affecting synovial and meniscus calcification phenotypes with 11 QTLs linked to synovial calcification. Functional and bioinformatic analyses of single nucleotide polymorphism identified functional classifications relevant to angiogenesis (Myo1e, Kif26b, Nprl3, Stab2, Fam105b), bone metabolism/calcification (Tle3, Tgfb2, Lipc, Nfe2l1, Ank, Fam105b), arthritis (Stab2, Tbx21, Map4k4, Hoxb9, Larp6, Col1a2, Adam10, Timp3, Nfe2l1, Trpm3), and ankylosing-spondylitis (Ank, Pon1, Il1r2, Tbkbp1) indicating that ectopic calcification involves multiple mechanisms. Furthermore, the expression of 11 candidate genes was significantly different between LG/J and SM/J. Correlation analysis showed that Aff3, Fam81a, Syn3, and Ank were correlated with synovial calcification. Our findings of multiple genetic loci affecting the phenotype suggest the involvement of multiple genes contributing to its pathogenesis. We collected tissue lysates from the formalin-fixed paraffin-embedded sections from mouse knee joints and analyzed the expression of several genes by Affymetrix QuantiGene Plex assay.

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Adapted Boolean Network Models for Extracellular Matrix Formation

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