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An integrated organoid omics map extends modeling potential of kidney disease

Author

Listed:
  • Moritz Lassé

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • 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)
    University Medical Center Hamburg-Eppendorf)

  • Dominik Kylies

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • Arvid Hutzfeldt

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • Léna Lydie Bonin

    (Aarhus University)

  • Bernhard Dumoulin

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • 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)
    University Medical Center Hamburg-Eppendorf)

  • Thorsten Wiech

    (University Medical Center Hamburg-Eppendorf
    University Medical Center Hamburg-Eppendorf (UKE))

  • Mercedes Noriega

    (University Medical Center Hamburg-Eppendorf
    University Medical Center Hamburg-Eppendorf (UKE))

  • Maria Chrysopoulou

    (Aarhus University)

  • Paul Brandts

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • Wenjun Ju

    (University of Michigan Medical School)

  • Linda Reinhard

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • Elion Hoxha

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • Florian Grahammer

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • Maja T. Lindenmeyer

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • Tobias B. Huber

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • 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)
    University Medical Center Hamburg-Eppendorf
    Aarhus University
    Aarhus University Hospital)

  • Fabian Braun

    (University Medical Center Hamburg-Eppendorf (UKE)
    University Medical Center Hamburg-Eppendorf)

  • Matthias Kretzler

    (University of Michigan Medical School
    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)
    University Medical Center Hamburg-Eppendorf
    Aarhus University
    Aarhus Institute of Advanced Studies (AIAS))

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.

Suggested Citation

  • 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 & Virgin, 2023. "An integrated organoid omics map extends modeling potential of kidney disease," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39740-7
    DOI: 10.1038/s41467-023-39740-7
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    References listed on IDEAS

    as
    1. Lorna J. Hale & Sara E. Howden & Belinda Phipson & Andrew Lonsdale & Pei X. Er & Irene Ghobrial & Salman Hosawi & Sean Wilson & Kynan T. Lawlor & Shahnaz Khan & Alicia Oshlack & Catherine Quinlan & Ra, 2018. "3D organoid-derived human glomeruli for personalised podocyte disease modelling and drug screening," Nature Communications, Nature, vol. 9(1), pages 1-17, December.
    2. Benjamin S. Freedman & Craig R. Brooks & Albert Q. Lam & Hongxia Fu & Ryuji Morizane & Vishesh Agrawal & Abdelaziz F. Saad & Michelle K. Li & Michael R. Hughes & Ryan Vander Werff & Derek T. Peters & , 2015. "Modelling kidney disease with CRISPR-mutant kidney organoids derived from human pluripotent epiblast spheroids," Nature Communications, Nature, vol. 6(1), pages 1-13, December.
    3. Ayshwarya Subramanian & Eriene-Heidi Sidhom & Maheswarareddy Emani & Katherine Vernon & Nareh Sahakian & Yiming Zhou & Maria Kost-Alimova & Michal Slyper & Julia Waldman & Danielle Dionne & Lan T. Ngu, 2019. "Single cell census of human kidney organoids shows reproducibility and diminished off-target cells after transplantation," Nature Communications, Nature, vol. 10(1), pages 1-15, December.
    4. Camilla Calandrini & Frans Schutgens & Rurika Oka & Thanasis Margaritis & Tito Candelli & Luka Mathijsen & Carola Ammerlaan & Ravian L. Ineveld & Sepide Derakhshan & Sanne Haan & Emmy Dolman & Philip , 2020. "An organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
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