Single-cell analysis reveals congruence between kidney organoids and human fetal kidney.

Alexander N Combes, Luke Zappia, Pei Xuan Er, Alicia Oshlack, Melissa H Little
Author Information
  1. Alexander N Combes: Department of Anatomy & Neuroscience, University of Melbourne, Melbourne, VIC, Australia. alexander.combes@unimelb.edu.au.
  2. Luke Zappia: Murdoch Children's Research Institute, Melbourne, VIC, Australia.
  3. Pei Xuan Er: Murdoch Children's Research Institute, Melbourne, VIC, Australia.
  4. Alicia Oshlack: Murdoch Children's Research Institute, Melbourne, VIC, Australia.
  5. Melissa H Little: Department of Anatomy & Neuroscience, University of Melbourne, Melbourne, VIC, Australia. melissa.little@mcri.edu.au. ORCID

Abstract

BACKGROUND: Human kidney organoids hold promise for studying development, disease modelling and drug screening. However, the utility of stem cell-derived kidney tissues will depend on how faithfully these replicate normal fetal development at the level of cellular identity and complexity.
METHODS: Here, we present an integrated analysis of single cell datasets from human kidney organoids and human fetal kidney to assess similarities and differences between the component cell types.
RESULTS: Clusters in the combined dataset contained cells from both organoid and fetal kidney with transcriptional congruence for key stromal, endothelial and nephron cell type-specific markers. Organoid enriched neural, glial and muscle progenitor populations were also evident. Major transcriptional differences between organoid and human tissue were likely related to technical artefacts. Cell type-specific comparisons revealed differences in stromal, endothelial and nephron progenitor cell types including expression of WNT2B in the human fetal kidney stroma.
CONCLUSIONS: This study supports the fidelity of kidney organoids as models of the developing kidney and affirms their potential in disease modelling and drug screening.

Keywords

References

  1. Nat Methods. 2019 Jan;16(1):79-87 [PMID: 30573816]
  2. Cell Stem Cell. 2017 Dec 7;21(6):730-746.e6 [PMID: 29129523]
  3. Development. 2017 Oct 1;144(19):3625-3632 [PMID: 28851704]
  4. PLoS One. 2011 Feb 28;6(2):e17286 [PMID: 21386911]
  5. Nat Methods. 2017 Oct;14(10):979-982 [PMID: 28825705]
  6. Dev Biol. 2018 Feb 1;434(1):36-47 [PMID: 29183737]
  7. Development. 1988 Dec;104(4):589-99 [PMID: 3268404]
  8. Development. 2017 Mar 15;144(6):958-962 [PMID: 28292841]
  9. F1000Res. 2016 Aug 31;5:2122 [PMID: 27909575]
  10. Nat Biotechnol. 2014 Apr;32(4):381-386 [PMID: 24658644]
  11. Dev Biol. 2003 Jan 1;253(1):109-24 [PMID: 12490201]
  12. Nat Biotechnol. 2015 Nov;33(11):1193-200 [PMID: 26458176]
  13. BMC Nephrol. 2012 Jul 28;13:70 [PMID: 22839765]
  14. J Am Soc Nephrol. 2018 Mar;29(3):806-824 [PMID: 29449449]
  15. Stem Cell Reports. 2014 Oct 14;3(4):650-62 [PMID: 25358792]
  16. Nat Protoc. 2016 Sep;11(9):1681-92 [PMID: 27560173]
  17. Pediatr Nephrol. 2014 Apr;29(4):695-704 [PMID: 24398540]
  18. Cell Stem Cell. 2014 Jan 2;14(1):53-67 [PMID: 24332837]
  19. Gigascience. 2018 Jul 1;7(7): [PMID: 30010766]
  20. Cell Stem Cell. 2018 Dec 6;23(6):869-881.e8 [PMID: 30449713]
  21. Nat Protoc. 2014 Oct;9(10):2329-40 [PMID: 25188634]
  22. Nature. 2015 Oct 22;526(7574):564-8 [PMID: 26444236]
  23. Development. 2016 Feb 15;143(4):595-608 [PMID: 26884396]
  24. Dev Cell. 2004 May;6(5):719-28 [PMID: 15130496]
  25. Development. 2014 Jan;141(1):17-27 [PMID: 24284212]
  26. Dev Biol. 2009 Aug 15;332(2):273-86 [PMID: 19501082]
  27. Nat Cell Biol. 2014 Jan;16(1):118-26 [PMID: 24335651]
  28. Dev Cell. 2018 Jun 4;45(5):651-660.e4 [PMID: 29870722]
  29. Genes Dev. 2004 Oct 15;18(20):2431-6 [PMID: 15489289]
  30. Nat Biotechnol. 2018 Jun;36(5):411-420 [PMID: 29608179]
  31. Nat Cell Biol. 2013 Sep;15(9):1035-44 [PMID: 23974041]
  32. Bioinformatics. 2017 Apr 15;33(8):1179-1186 [PMID: 28088763]
  33. Stem Cell Reports. 2018 Aug 14;11(2):470-484 [PMID: 30033089]
  34. Methods. 2015 Sep 1;85:54-61 [PMID: 26142758]
  35. Blood. 2012 May 24;119(21):4823-7 [PMID: 22415753]
  36. Cell. 1996 Sep 20;86(6):897-906 [PMID: 8808625]
  37. Dev Cell. 2014 Apr 28;29(2):188-202 [PMID: 24780737]
  38. Nucleic Acids Res. 2015 Jul 1;43(W1):W589-98 [PMID: 25897122]
  39. Nat Commun. 2015 Oct 23;6:8715 [PMID: 26493500]
  40. Bioinformatics. 2005 Aug 15;21(16):3439-40 [PMID: 16082012]
  41. Science. 2018 Aug 10;361(6402):594-599 [PMID: 30093597]
  42. Nature. 2016 Aug 11;536(7615):238 [PMID: 27120161]
  43. Neural Comput. 2004 Dec;16(12):2639-64 [PMID: 15516276]
  44. Stem Cells. 2013 Mar;31(3):467-78 [PMID: 23225669]
  45. Nucleic Acids Res. 2009 Jul;37(Web Server issue):W305-11 [PMID: 19465376]
  46. Nat Biotechnol. 2015 May;33(5):495-502 [PMID: 25867923]

Grants

  1. DK107344/NIDDK NIH HHS
  2. UH2 DK107344/NIDDK NIH HHS
  3. UH3 DK107344/NIDDK NIH HHS

MeSH Term

Cell Line
Cell Lineage
Glycoproteins
Humans
Induced Pluripotent Stem Cells
Kidney
Organoids
Single-Cell Analysis
Wnt Proteins

Chemicals

Glycoproteins
WNT2B protein, human
Wnt Proteins