An integrated organoid omics map extends modeling potential of kidney disease

Moritz Lassé, Jamal El Saghir, Celine C. Berthier, Sean Eddy, Matthew Fischer, Sandra D. Laufer, Dominik Kylies, Arvid Hutzfeldt, Léna Lydie Bonin, Bernhard Dumoulin, Rajasree Menon, Virginia Vega-Warner, Felix Eichinger, Fadhl Alakwaa, Damian Fermin, Anja M. Billing, Akihiro Minakawa, Phillip J. McCown, Michael P. Rose, Bradley Godfrey, Elisabeth Meister, Thorsten Wiech, Mercedes Noriega, Maria Chrysopoulou, Paul Brandts, Wenjun Ju, Linda Reinhard, Elion Hoxha, Florian Grahammer, Maja T. Lindenmeyer, Tobias B. Huber, Hartmut Schlüter, Steffen Thiel, Laura H. Mariani, Victor G. Puelles, Fabian Braun, Matthias Kretzler, Fatih Demir, Jennifer L. Harder () and Markus M. Rinschen ()
Additional contact information
Moritz Lassé: University Medical Center Hamburg-Eppendorf (UKE)
Jamal El Saghir: University of Michigan Medical School
Celine C. Berthier: University of Michigan Medical School
Sean Eddy: University of Michigan Medical School
Matthew Fischer: University of Michigan Medical School
Sandra D. Laufer: University Medical Center Hamburg-Eppendorf (UKE)
Dominik Kylies: University Medical Center Hamburg-Eppendorf (UKE)
Arvid Hutzfeldt: University Medical Center Hamburg-Eppendorf (UKE)
Léna Lydie Bonin: Aarhus University
Bernhard Dumoulin: University Medical Center Hamburg-Eppendorf (UKE)
Rajasree Menon: University of Michigan Medical School
Virginia Vega-Warner: University of Michigan Medical School
Felix Eichinger: University of Michigan Medical School
Fadhl Alakwaa: University of Michigan Medical School
Damian Fermin: University of Michigan Medical School
Anja M. Billing: Aarhus University
Akihiro Minakawa: University of Michigan Medical School
Phillip J. McCown: University of Michigan Medical School
Michael P. Rose: University of Michigan Medical School
Bradley Godfrey: University of Michigan Medical School
Elisabeth Meister: University Medical Center Hamburg-Eppendorf (UKE)
Thorsten Wiech: University Medical Center Hamburg-Eppendorf
Mercedes Noriega: University Medical Center Hamburg-Eppendorf
Maria Chrysopoulou: Aarhus University
Paul Brandts: University Medical Center Hamburg-Eppendorf (UKE)
Wenjun Ju: University of Michigan Medical School
Linda Reinhard: University Medical Center Hamburg-Eppendorf (UKE)
Elion Hoxha: University Medical Center Hamburg-Eppendorf (UKE)
Florian Grahammer: University Medical Center Hamburg-Eppendorf (UKE)
Maja T. Lindenmeyer: University Medical Center Hamburg-Eppendorf (UKE)
Tobias B. Huber: University Medical Center Hamburg-Eppendorf (UKE)
Hartmut Schlüter: University Medical Center Hamburg-Eppendorf (UKE)
Steffen Thiel: Aarhus University
Laura H. Mariani: University of Michigan Medical School
Victor G. Puelles: University Medical Center Hamburg-Eppendorf (UKE)
Fabian Braun: University Medical Center Hamburg-Eppendorf (UKE)
Matthias Kretzler: University of Michigan Medical School
Fatih Demir: Aarhus University
Jennifer L. Harder: University of Michigan Medical School
Markus M. Rinschen: University Medical Center Hamburg-Eppendorf (UKE)

Nature Communications, 2023, vol. 14, issue 1, 1-21

Abstract: Abstract 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.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39740-7

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DOI: 10.1038/s41467-023-39740-7

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