In silico nano-dissection: defining cell type specificity at transcriptional level in human disease (glomeruli)
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ABSTRACT: To identify genes with cell-lineage-specific expression not accessible by experimental micro-dissection, we developed a genome-scale iterative method, in-silico nano-dissection, which leverages high-throughput functional-genomics data from tissue homogenates using a machine-learning framework. This study applied nano-dissection to chronic kidney disease and identified transcripts specific to podocytes, key cells in the glomerular filter responsible for hereditary proteinuric syndromes and acquired CKD. In-silico prediction accuracy exceeded predictions derived from fluorescence-tagged-murine podocytes, identified genes recently implicated in hereditary glomerular disease and predicted genes significantly correlated with kidney function. The nano-dissection method is broadly applicable to define lineage specificity in many functional and disease contexts. We applied a machine-learning framework on high-throughput gene expression data from human kidney biopsy tissue homogenates and predict novel podocyte-specific genes. The prediction was validated by Human Protein Atlas at protein level. Prediction accuracy was compared with predictions derived from experimental approach using fluorescence-tagged-murine podocytes.
Project description:To identify genes with cell-lineage-specific expression not accessible by experimental micro-dissection, we developed a genome-scale iterative method, in-silico nano-dissection, which leverages high-throughput functional-genomics data from tissue homogenates using a machine-learning framework. This study applied nano-dissection to chronic kidney disease and identified transcripts specific to podocytes, key cells in the glomerular filter responsible for hereditary proteinuric syndromes and acquired CKD. In-silico prediction accuracy exceeded predictions derived from fluorescence-tagged-murine podocytes, identified genes recently implicated in hereditary glomerular disease and predicted genes significantly correlated with kidney function. The nano-dissection method is broadly applicable to define lineage specificity in many functional and disease contexts. We applied a machine-learning framework on high-throughput gene expression data from human kidney biopsy tissue homogenates and predict novel podocyte-specific genes. The prediction was validated by Human Protein Atlas at protein level. Prediction accuracy was compared with predictions derived from experimental approach using fluorescence-tagged-murine podocytes.
Project description:To identify genes with cell-lineage-specific expression not accessible by experimental micro-dissection, we developed a genome-scale iterative method, in-silico nano-dissection, which leverages high-throughput functional-genomics data from tissue homogenates using a machine-learning framework. This study applied nano-dissection to chronic kidney disease and identified transcripts specific to podocytes, key cells in the glomerular filter responsible for hereditary proteinuric syndromes and acquired CKD. In-silico prediction accuracy exceeded predictions derived from fluorescence-tagged-murine podocytes, identified genes recently implicated in hereditary glomerular disease and predicted genes significantly correlated with kidney function. The nano-dissection method is broadly applicable to define lineage specificity in many functional and disease contexts.
Project description:To identify genes with cell-lineage-specific expression not accessible by experimental micro-dissection, we developed a genome-scale iterative method, in-silico nano-dissection, which leverages high-throughput functional-genomics data from tissue homogenates using a machine-learning framework. This study applied nano-dissection to chronic kidney disease and identified transcripts specific to podocytes, key cells in the glomerular filter responsible for hereditary proteinuric syndromes and acquired CKD. In-silico prediction accuracy exceeded predictions derived from fluorescence-tagged-murine podocytes, identified genes recently implicated in hereditary glomerular disease and predicted genes significantly correlated with kidney function. The nano-dissection method is broadly applicable to define lineage specificity in many functional and disease contexts.
Project description:Podocytes, highly differentiated glomerular epithelial cells, are essential for the maintenance of glomerular filtration barrier. Podocyte dysfunction in podocytes is a major determinant of proteinuric kidney disease. By RNA sequencing analysis in ADR-treated podocytes with or without MYDGF overexpression, we observed the significant changes of genes important in regulating cell cycle in podocytes with ADR treatment.
Project description:The specialized glomerular epithelial cell (podocyte) of the kidney is a complex cell that is often damaged in glomerular diseases. Study of this cell type is facilitated by an in vitro system of propagation of conditionally immortalized podocytes. Here, genes that are differentially expressed in this in vitro model of podocyte differentiation are evaluated. Conditionally immortalized undifferentiated mouse podocytes were cultured under permissive conditions at 33*C. Podocytes that were differentiated at the non-permissive conditions at 37*C were used for comparison.
Project description:Podocytes, highly differentiated glomerular epithelial cells, are essential for the maintenance of glomerular filtration barrier. Lipid accumulation in podocytes is a major determinant of proteinuric kidney disease. By RNA-sequencing analysis, we observed the significant changes of genes important in regulating cellular lipid homeostasis in podocytes with HG treatment. We generated two mouse podocyte cell lines stably transduced with either a sh-NC lentiviral construct or a shRNA lentiviral construct designed to target JAML RNA to investigate the consequences on the gene expression profile of JAML knockdown in mouse podocytes.
Project description:Glomerular diseases are the leading cause of chronic kidney diseases with pathomechanisms largely unclear. It is known that ANGPT2 regulates endothelial cell homeostasis and function via TEK/TIE2 and its deregulation causes endothelial damage. We found that ANGPT2 is upregulated in glomerular diseases and wondered whether it has any effect on glomerular podocytes and mesangial cells given that they have no or low TEK expression. We treated podocytes and mesangial cells in culture with ANGPT2 and found no overt cellular changes. RNA-seq analysis showed that gene expression was altered in both podocytes and mesangial cells and that the regulated genes in the two cell types were fundamentally different. GO and KEGG analyses showed that the two groups of regulated genes were enriched in distinct processes and pathways. These results suggest that ANGPT2 exerts effects on both podocytes and mesangial cells and that increased ANGPT2 may be involved in glomerular injury by affecting podocytes and mesangial cells in addition to endothelial cells.
Project description:Glomerular diseases are the leading cause of chronic kidney diseases with pathomechanisms largely unclear. It is known that ANGPT2 regulates endothelial cell homeostasis and function via TEK/TIE2 and its deregulation causes endothelial damage. We found that ANGPT2 is upregulated in glomerular diseases and wondered whether it has any effect on glomerular podocytes and mesangial cells given that they have no or low TEK expression. We treated podocytes and mesangial cells in culture with ANGPT2 and found no overt cellular changes. RNA-seq analysis showed that gene expression was altered in both podocytes and mesangial cells and that the regulated genes in the two cell types were fundamentally different. GO and KEGG analyses showed that the two groups of regulated genes were enriched in distinct processes and pathways. These results suggest that ANGPT2 exerts effects on both podocytes and mesangial cells and that increased ANGPT2 may be involved in glomerular injury by affecting podocytes and mesangial cells in addition to endothelial cells.
Project description:We used a highly sensitive nano-5hmC-Seal method and profiled the genome-wide distribution of 5-hydroxymethylcytosine (5hmC) in plasma cell-free DNA (cfDNA) from 384 patients with bladder, breast, colorectal, kidney, lung, or prostate cancer and 221 controls. We used machine learning and developed plasma cfDNA 5hmC signatures that are highly sensitive for cancer detection and cancer origin determination. We also identified genes and signaling pathways with aberrant DNA hydroxymethylation in six cancers.
Project description:Podocytes are the highly specialised cells within the glomeruli of the kidney that maintain the filtration barrier by forming interdigitating foot processes and slit-diaphragms. Disruption to these features result in proteinuria. Studies into podocyte biology and disease has been hampered by a paucity of in vitro models of this non-proliferative cell type. Here we characterise sieved glomeruli from kidney organoids derived from human pluripotent stem cells. Compared to conditionally immortalised podocytes, organoid-derived glomeruli show superior podocyte-specific gene and protein expression, morphology and functional properties. Using CRISPR-derived MAFB reporter iPSC lines, homozygous MAFB mutant organoids recapitulated the anticipated disease related transcriptional changes. Culture of kidney organoids on chicken chorioallantoic membrane resulted in glomerular vascularisation, glomerular filtration barrier assembly, formation of slit diaphragms and fenestrated endothelial cells. This definitively demonstrates that human iPSC kidney organoid-derived glomeruli can serve as an accurate model of human podocytopathies and glomerular disease in vitro.