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An integrated organoid omics map extends modeling potential of kidney disease.

Moritz LasséJamal El SaghirCeline C BerthierSean EddyMatthew FischerSandra D LauferDominik KyliesArvid D HutzfeldtLéna Lydie BoninBernhard DumoulinRajasree MenonVirginia Vega-WarnerFelix EichingerFadhl M Al-AkwaaDamian FerminAnja M BillingAkihiro MinakawaPhillip J McCownMichael P RoseBradley GodfreyElisabeth MeisterThorsten WiechMercedes NoriegaMaria ChrysopoulouPaul BrandtsWenjun JuLinda ReinhardElion HoxhaFlorian GrahammerMaja T LindenmeyerTobias B HuberHartmut SchlüterSteffen ThielLaura H MarianiVictor G PuellesFabian BraunMatthias KretzlerFatih DemirJennifer L HarderMarkus M Rinschen
Published in: Nature communications (2023)
Kidney organoids are a promising model to study kidney disease, but their use is constrained by limited knowledge of their functional protein expression profile. Here, we define the organoid proteome and transcriptome trajectories over culture duration and upon exposure to TNFα, a cytokine stressor. Older organoids increase deposition of extracellular matrix but decrease expression of glomerular proteins. Single cell transcriptome integration reveals that most proteome changes localize to podocytes, tubular and stromal cells. TNFα treatment of organoids results in 322 differentially expressed proteins, including cytokines and complement components. Transcript expression of these 322 proteins is significantly higher in individuals with poorer clinical outcomes in proteinuric kidney disease. Key TNFα-associated protein (C3 and VCAM1) expression is increased in both human tubular and organoid kidney cell populations, highlighting the potential for organoids to advance biomarker development. By integrating kidney organoid omic layers, incorporating a disease-relevant cytokine stressor and comparing with human data, we provide crucial evidence for the functional relevance of the kidney organoid model to human kidney disease.
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