ZFIN ID: ZDB-PUB-180526-7
A Multi-layered Quantitative In Vivo Expression Atlas of the Podocyte Unravels Kidney Disease Candidate Genes
Rinschen, M.M., Gödel, M., Grahammer, F., Zschiedrich, S., Helmstädter, M., Kretz, O., Zarei, M., Braun, D.A., Dittrich, S., Pahmeyer, C., Schroder, P., Teetzen, C., Gee, H., Daouk, G., Pohl, M., Kuhn, E., Schermer, B., Küttner, V., Boerries, M., Busch, H., Schiffer, M., Bergmann, C., Krüger, M., Hildebrandt, F., Dengjel, J., Benzing, T., Huber, T.B.
Date: 2018
Source: Cell Reports   23: 2495-2508 (Journal)
Registered Authors: Hildebrandt, Friedhelm
Keywords: end-stage renal disease, focal segmental glomerulosclerosis, hereditary nephrotic syndrome, kinase, metabolism, proteinuria, proteostasis, pulse SILAC, slit diaphragm, systems biology
MeSH Terms:
  • Animals
  • Base Sequence
  • Cells, Cultured
  • Gene Expression Regulation*
  • Genetic Association Studies*
  • Humans
  • Kidney Diseases/genetics*
  • Mice
  • Podocytes/metabolism*
  • Proteome/metabolism
  • Transcriptome/genetics
  • Zebrafish
PubMed: 29791858 Full text @ Cell Rep.
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ABSTRACT
Damage to and loss of glomerular podocytes has been identified as the culprit lesion in progressive kidney diseases. Here, we combine mass spectrometry-based proteomics with mRNA sequencing, bioinformatics, and hypothesis-driven studies to provide a comprehensive and quantitative map of mammalian podocytes that identifies unanticipated signaling pathways. Comparison of the in vivo datasets with proteomics data from podocyte cell cultures showed a limited value of available cell culture models. Moreover, in vivo stable isotope labeling by amino acids uncovered surprisingly rapid synthesis of mitochondrial proteins under steady-state conditions that was perturbed under autophagy-deficient, disease-susceptible conditions. Integration of acquired omics dimensions suggested FARP1 as a candidate essential for podocyte function, which could be substantiated by genetic analysis in humans and knockdown experiments in zebrafish. This work exemplifies how the integration of multi-omics datasets can identify a framework of cell-type-specific features relevant for organ health and disease.
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