Kidney Metabolism Modeling System (Kidney on a Chip)
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA497705 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Kidney Metabolism Modeling System (Kidney on a Chip)
| PRJNA497704 | ENA
Project description:Modeling oxidative injury response in human kidney organoids
| PRJNA755987 | ENA
Project description:Kidney fibrosis, characterized by excessive extracellular matrix (ECM) deposition, is a progressive disease that, despite affecting 10% of the population, lacks specific treatments and suitable biomarkers. Aimed at unraveling disease mechanisms and identifying potential therapeutic targets, this study presents a comprehensive, time-resolved multi-omics analysis of kidney fibrosis using an in vitro model system based on human kidney PDGFRβ+ mesenchymal cells. Using computational network modeling we integrated transcriptomics, proteomics, phosphoproteomics, and secretomics with imaging of the extracellular matrix (ECM). We quantified over 14,000 biomolecules across seven time points following TGF-β stimulation, revealing distinct temporal patterns in the expression and activity of known and potential novel renal fibrosis markers and modulators. The resulting time-resolved multi-omic network models allowed us to propose mechanisms related to fibrosis progression through early transcriptional reprogramming. Using siRNA knockdowns and phenotypic assays, we validated predictions and elucidated regulatory mechanisms underlying kidney fibrosis. Notably, we demonstrate that several early-activated transcription factors, including FLI1 and E2F1, act as negative regulators of collagen deposition and propose underlying molecular mechanisms. This work advances our understanding of the pathogenesis of kidney fibrosis and provides a valuable resource for the organ fibrosis research community.
2024-11-07 | E-MTAB-14521 | biostudies-arrayexpress
Project description:Kidney fibrosis, characterized by excessive extracellular matrix (ECM) deposition, is a progressive disease that, despite affecting 10% of the population, lacks specific treatments and suitable biomarkers. Aimed at unraveling disease mechanisms and identifying potential therapeutic targets, this study presents a comprehensive, time-resolved multi-omics analysis of kidney fibrosis using an in vitro model system based on human kidney PDGFRβ+ mesenchymal cells. Using computational network modeling we integrated transcriptomics, proteomics, phosphoproteomics, and secretomics with imaging of the extracellular matrix (ECM). We quantified over 14,000 biomolecules across seven time points following TGF-β stimulation, revealing distinct temporal patterns in the expression and activity of known and potential novel renal fibrosis markers and modulators. The resulting time-resolved multi-omic network models allowed us to propose mechanisms related to fibrosis progression through early transcriptional reprogramming. Using siRNA knockdowns and phenotypic assays, we validated predictions and elucidated regulatory mechanisms underlying kidney fibrosis. Notably, we demonstrate that several early-activated transcription factors, including FLI1 and E2F1, act as negative regulators of collagen deposition and propose underlying molecular mechanisms. This work advances our understanding of the pathogenesis of kidney fibrosis and provides a valuable resource for the organ fibrosis research community.
2025-04-08 | PXD056096 | Pride
Project description:Microphysiological System Modeling of Ochratoxin A-Associated Nephrotoxicity
| PRJNA637238 | ENA
Project description:Polymyxin nephrotoxicity in kidney chip
| PRJNA508797 | ENA
Project description:Ochratoxin A (OTA) is one of the most abundant mycotoxin contaminants in food stuffs and possesses carcinogenic, nephrotoxic, teratogenic and immunotoxic properties. Especially, severe nephrotoxicity is of great concern, as characterized by degeneration of epithelial cells of the proximal tubules and interstitial fibrosis. However, its mechanism of toxicity, hazard identification as well as genetic risk factors contributing to OTA toxicity in humans has been elusive due to the lack of adequate models that fully recapitulate kidney function in vitro. The present study attempts to evaluate dose-response relationships, identify the contribution of active transport proteins that govern renal disposition of OTA, and determine the role of metabolism in bioactivation and detoxification of OTA using a 3D human kidney proximal tubule microphysiological system (kidney MPS). We demonstrated that IC50 values of OTA in kidney MPS culture (0.375 – 1.21 µM) were in good agreement with clinical toxic concentrations of OTA in urine. Surprisingly, no enhancement of kidney injury biomarkers was evident in the effluents of kidney MPS after OTA exposure despite significant toxicity observed by LIVE/DEAD staining, rather these biomarkers were decreased in OTA concentration-dependent manner. Furthermore, the effect of 1-aminobenzotriazole (ABT) and 6-(NBD-4-ylthio-) hexanol (NBDHEX), pan-inhibitor of P450 and GST enzymes, respectively, on the OTA-induced toxicity in kidney MPS was examined, which resulted in significant enhancement of OTA-induced toxicity by NBDHEX (3 µM) treatment whereas ABT (1 mM) treatment decreased OTA-induced toxicity, suggesting the roles of GSTs and P450 enzymes in the detoxification and bioactivation of OTA, respectively. Additionally, OTA transport studies using kidney MPS in the presence and absence of inhibitor of organic anion transporter(s), probenecid (1 mM), revealed the role of organic anionic membrane transporter(s) in the kidney specific disposition of OTA. Our findings provide a better understanding of the mechanism of OTA-induced kidney injury which may support changes in risk assessment, regulatory agency policies on allowable exposure levels and determination of genetic factors in high-risk populations against OTA nephrotoxicity.
2020-10-22 | GSE151776 | GEO
Project description:Mangrove-derived Streptomyces xiamenensis 318, with a relatively compact genome and simpler secondary metabolism, is used as model organism in our investigation. We performed integrated studies of metabolic dynamical modeling, transcriptome level measurements, and metabolic profiling experiments on this strain. To explore the relationship between primary and secondary metabolism, the global gene expression levels of strain 318 from early stationary phase to late stationary phase were compared by RNAseq analysis at 16 hour, 24 hour, 36 hour and 72 hour after batch culture started.
2019-02-10 | E-MTAB-7314 | biostudies-arrayexpress
Project description:Modeling epigenetic lesions that cause gliomas [ChIP-Seq]
| PRJNA937235 | ENA
Project description:An integrated organoid omics map extends modeling potential of kidney disease
| PRJNA883395 | ENA