Project description:Expression data from peritoneal biopsies of patients with encapsulating peritoneal sclerosis (EPS), patients undergoing first implantation of a peritoneal dialysis catheter (PD), and patients undergoing abdominal surgery for non-peritoneal conditions (controls) We used microarrays to determine the transcriptional profiles of peritoneal membrane in patients with encapsulating peritoneal sclerosis (EPS), patients undergoing first insertion of a peritoneal dialysis cathetier (PD), and uremic patients without history of PD or EPS, undergoing abdominal surgery for non-peritoneal problems (CON) Encapsulating peritoneal sclerosis (EPS) is a devastating complication of peritoneal dialysis (PD), characterized by marked inflammation and severe fibrosis of the peritoneum, and associated with high morbidity and mortality. EPS can occur years after termination of PD and, in severe cases, leads to intestinal obstruction and ileus requiring surgical intervention. Despite ongoing research, the pathogenesis of EPS remains unclear. We performed a global transcriptome analysis of peritoneal tissue specimens from EPS patients, PD patients without EPS, and uremic patients without history of PD or EPS (Uremic). Unsupervised and supervised bioinformatics analysis revealed distinct transcriptional patterns that discriminated these three clinical groups. The analysis identified a signature of 219 genes expressed differentially in EPS as compared to PD and Uremic groups. Canonical pathway analysis of differentially expressed genes showed enrichment in several pathways, including antigen presentation, dendritic cell maturation, B cell development, chemokine signaling and humoral and cellular immunity (P value <0.05). Further interactive network analysis depicted effects of EPS-associated genes on networks linked to inflammation, immunological response, and cell proliferation. Gene expression changes were confirmed by qRT-PCR for a subset of the differentially expressed genes. EPS patient tissues exhibited elevated expression of genes encoding sulfatase1, thrombospondin 1, fibronectin 1 and alpha smooth muscle actin, among many others, while in EPS and PD tissues mRNAs encoding leptin and retinol-binding protein 4 were markedly down-regulated, compared to Uremic group patients. Immunolocalization of Collagen 1 alpha 1 revealed that Col1a1 protein was predominantly expressed in the submesothelial compact zone of EPS patient peritoneal samples, whereas PD patient peritoneal samples exhibited homogenous Col1a1 staining throughout the tissue samples. The results are compatible with the hypothesis that encapsulating peritoneal sclerosis is a distinct pathological process from the simple peritoneal fibrosis that accompanies all PD treatment. Total RNA was isolated from frozen peritoneal biopsy specimens obtained at time of surgery. RNA was hybridized to Affymetrix arrays, and analyzed. Select transcripts were subjected to validation by rt-pcr and by immunodetection.

Project description:Expression data from peritoneal biopsies of patients with encapsulating peritoneal sclerosis (EPS), patients undergoing first implantation of a peritoneal dialysis catheter (PD), and patients undergoing abdominal surgery for non-peritoneal conditions (controls) We used microarrays to determine the transcriptional profiles of peritoneal membrane in patients with encapsulating peritoneal sclerosis (EPS), patients undergoing first insertion of a peritoneal dialysis cathetier (PD), and uremic patients without history of PD or EPS, undergoing abdominal surgery for non-peritoneal problems (CON) Encapsulating peritoneal sclerosis (EPS) is a devastating complication of peritoneal dialysis (PD), characterized by marked inflammation and severe fibrosis of the peritoneum, and associated with high morbidity and mortality. EPS can occur years after termination of PD and, in severe cases, leads to intestinal obstruction and ileus requiring surgical intervention. Despite ongoing research, the pathogenesis of EPS remains unclear. We performed a global transcriptome analysis of peritoneal tissue specimens from EPS patients, PD patients without EPS, and uremic patients without history of PD or EPS (Uremic). Unsupervised and supervised bioinformatics analysis revealed distinct transcriptional patterns that discriminated these three clinical groups. The analysis identified a signature of 219 genes expressed differentially in EPS as compared to PD and Uremic groups. Canonical pathway analysis of differentially expressed genes showed enrichment in several pathways, including antigen presentation, dendritic cell maturation, B cell development, chemokine signaling and humoral and cellular immunity (P value <0.05). Further interactive network analysis depicted effects of EPS-associated genes on networks linked to inflammation, immunological response, and cell proliferation. Gene expression changes were confirmed by qRT-PCR for a subset of the differentially expressed genes. EPS patient tissues exhibited elevated expression of genes encoding sulfatase1, thrombospondin 1, fibronectin 1 and alpha smooth muscle actin, among many others, while in EPS and PD tissues mRNAs encoding leptin and retinol-binding protein 4 were markedly down-regulated, compared to Uremic group patients. Immunolocalization of Collagen 1 alpha 1 revealed that Col1a1 protein was predominantly expressed in the submesothelial compact zone of EPS patient peritoneal samples, whereas PD patient peritoneal samples exhibited homogenous Col1a1 staining throughout the tissue samples. The results are compatible with the hypothesis that encapsulating peritoneal sclerosis is a distinct pathological process from the simple peritoneal fibrosis that accompanies all PD treatment.

Project description:Wodke2013 - Genome-scale constraint-based model of M.pneumoniae energy metabolism (iJW145) A new genome-scale metabolic reconstruction of M.pneumoniae is used in combination with external metabolite measurement and protein abundance measurements to quantitatively explore the energy metabolism of this genome-reduce human pathogen. This model is described in the article: Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling. Wodke JA, Puchałka J, Lluch-Senar M, Marcos J, Yus E, Godinho M, Gutiérrez-Gallego R, dos Santos VA, Serrano L, Klipp E, Maier T. Mol Syst Biol. 2013;9:653. Abstract: Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint-based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time-dependent changes, albeit using a static model. By performing an in silico knock-out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms. This model is hosted on BioModels Database and identified by: MODEL1301290000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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