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Kidney and organoid single-cell transcriptomics: the end of the beginning

  • Parker C. Wilson
  • Benjamin D. HumphreysEmail author
Review

Abstract

Single-cell RNA sequencing (scRNA-seq) technologies are increasingly being applied to reveal cellular heterogeneity in kidney development and disease. In just the last year, multiple scRNA-seq datasets have been generated from kidney organoids, developing mouse and human kidney, adult kidney, and kidney cancer. The data generated enables a much deeper understanding of biological processes within and between cells. It has also elucidated unforeseen cell lineage relationships, defined the presence of off-target cell types in kidney organoids, and revealed a diverse inflammatory response in a human kidney allograft undergoing rejection. This review summarizes the recent rapid progress in scRNA-seq of the kidney and outlines future directions for single-cell technologies as applied to the kidney.

Keywords

Next-generation sequencing Transcriptomics Single cell Informatics Organoids Stem cell 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Malone AF, Wu H, Humphreys BD (2018) Bringing renal biopsy interpretation into the molecular age with single-cell RNA sequencing. Semin Nephrol 38:31–39CrossRefGoogle Scholar
  2. 2.
    Zheng GX, Terry JM, Belgrader P, Ryvkin P, Bent ZW, Wilson R, Ziraldo SB, Wheeler TD, McDermott GP, Zhu J, Gregory MT, Shuga J, Montesclaros L, Underwood JG, Masquelier DA, Nishimura SY, Schnall-Levin M, Wyatt PW, Hindson CM, Bharadwaj R, Wong A, Ness KD, Beppu LW, Deeg HJ, McFarland C, Loeb KR, Valente WJ, Ericson NG, Stevens EA, Radich JP, Mikkelsen TS, Hindson BJ, Bielas JH (2017) Massively parallel digital transcriptional profiling of single cells. Nat Commun 8:14049CrossRefGoogle Scholar
  3. 3.
    Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, Tirosh I, Bialas AR, Kamitaki N, Martersteck EM, Trombetta JJ, Weitz DA, Sanes JR, Shalek AK, Regev A, McCarroll SA (2015) Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161:1202–1214CrossRefGoogle Scholar
  4. 4.
    Klein AM, Mazutis L, Akartuna I, Tallapragada N, Veres A, Li V, Peshkin L, Weitz DA, Kirschner MW (2015) Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161:1187–1201CrossRefGoogle Scholar
  5. 5.
    Han X, Wang R, Zhou Y, Fei L, Sun H, Lai S, Saadatpour A, Zhou Z, Chen H, Ye F, Huang D, Xu Y, Huang W, Jiang M, Jiang X, Mao J, Chen Y, Lu C, Xie J, Fang Q, Wang Y, Yue R, Li T, Huang H, Orkin SH, Yuan GC, Chen M, Guo G (2018) Mapping the mouse cell atlas by Microwell-Seq. Cell 172(1091–1107):e1017Google Scholar
  6. 6.
    Hedlund E, Deng Q (2018) Single-cell RNA sequencing: technical advancements and biological applications. Mol Asp Med 59:36–46CrossRefGoogle Scholar
  7. 7.
    Wu H, Humphreys BD (2017) The promise of single-cell RNA sequencing for kidney disease investigation. Kidney Int 92:1334–1342CrossRefGoogle Scholar
  8. 8.
    Park J, Shrestha R, Qiu C, Kondo A, Huang S, Werth M, Li M, Barasch J, Susztak K (2018) Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease. Science 360:758–763CrossRefGoogle Scholar
  9. 9.
    Humphreys BD (2018) Mapping kidney cellular complexity. Science 360:709–710CrossRefGoogle Scholar
  10. 10.
    Karaiskos N, Rahmatollahi M, Boltengagen A, Liu H, Hoehne M, Rinschen M, Schermer B, Benzing T, Rajewsky N, Kocks C, Kann M, Muller RU (2018) A single-cell transcriptome atlas of the mouse glomerulus. J Am Soc Nephrol 29:2060–2068CrossRefGoogle Scholar
  11. 11.
    Sivakamasundari V, Bolisetty M, Sivajothi S, Bessonett S, Ruan D, Robson P (2017) Comprehensive cell type specific transcriptomics of the human kidney. bioRxiv.  https://doi.org/10.1101/238063
  12. 12.
    Morita K, Sasaki H, Furuse M, Tsukita S (1999) Endothelial claudin: claudin-5/TMVCF constitutes tight junction strands in endothelial cells. J Cell Biol 147:185–194CrossRefGoogle Scholar
  13. 13.
    Abramsson A, Lindblom P, Betsholtz C (2003) Endothelial and nonendothelial sources of PDGF-B regulate pericyte recruitment and influence vascular pattern formation in tumors. J Clin Invest 112:1142–1151CrossRefGoogle Scholar
  14. 14.
    Lin SL, Chang FC, Schrimpf C, Chen YT, Wu CF, Wu VC, Chiang WC, Kuhnert F, Kuo CJ, Chen YM, Wu KD, Tsai TJ, Duffield JS (2011) Targeting endothelium-pericyte cross talk by inhibiting VEGF receptor signaling attenuates kidney microvascular rarefaction and fibrosis. Am J Pathol 178:911–923CrossRefGoogle Scholar
  15. 15.
    Chen L, Lee JW, Chou CL, Nair AV, Battistone MA, Paunescu TG, Merkulova M, Breton S, Verlander JW, Wall SM, Brown D, Burg MB, Knepper MA (2017) Transcriptomes of major renal collecting duct cell types in mouse identified by single-cell RNA-seq. Proc Natl Acad Sci U S A 114:E9989–E9998CrossRefGoogle Scholar
  16. 16.
    Gillies CE, Putler R, Menon R, Otto E, Yasutake K, Nair V, Hoover P, Lieb D, Li S, Eddy S, Fermin D, MT MN, Nephrotic Syndrome Study N, Hacohen N, Kiryluk K, Kretzler M, Wen X, Sampson MG (2018) An eQTL landscape of kidney tissue in human nephrotic syndrome. Am J Hum Genet 103:232–244CrossRefGoogle Scholar
  17. 17.
    Gbadegesin RA, Adeyemo A, Webb NJ, Greenbaum LA, Abeyagunawardena A, Thalgahagoda S, Kale A, Gipson D, Srivastava T, Lin JJ, Chand D, Hunley TE, Brophy PD, Bagga A, Sinha A, Rheault MN, Ghali J, Nicholls K, Abraham E, Janjua HS, Omoloja A, Barletta GM, Cai Y, Milford DD, O'Brien C, Awan A, Belostotsky V, Smoyer WE, Homstad A, Hall G, Wu G, Nagaraj S, Wigfall D, Foreman J, Winn MP, Mid-West Pediatric Nephrology C (2015) HLA-DQA1 and PLCG2 are candidate risk loci for childhood-onset steroid-sensitive nephrotic syndrome. J Am Soc Nephrol 26:1701–1710CrossRefGoogle Scholar
  18. 18.
    Gissen P, Johnson CA, Morgan NV, Stapelbroek JM, Forshew T, Cooper WN, McKiernan PJ, Klomp LW, Morris AA, Wraith JE, McClean P, Lynch SA, Thompson RJ, Lo B, Quarrell OW, Di Rocco M, Trembath RC, Mandel H, Wali S, Karet FE, Knisely AS, Houwen RH, Kelly DA, Maher ER (2004) Mutations in VPS33B, encoding a regulator of SNARE-dependent membrane fusion, cause arthrogryposis-renal dysfunction-cholestasis (ARC) syndrome. Nat Genet 36:400–404CrossRefGoogle Scholar
  19. 19.
    Wu H, Malone AF, Donnelly EL, Kirita Y, Uchimura K, Ramakrishnan SM, Gaut JP, Humphreys BD (2018) Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response. J Am Soc Nephrol 29:2069–2080CrossRefGoogle Scholar
  20. 20.
    van den Bosch TPP, Hilbrands LB, Kraaijeveld R, Litjens NHR, Rezaee F, Nieboer D, Steyerberg EW, van Gestel JA, Roelen DL, Clahsen-van Groningen MC, Baan CC, Rowshani AT (2017) Pretransplant numbers of CD16(+) monocytes as a novel biomarker to predict acute rejection after kidney transplantation: a pilot study. Am J Transplant 17:2659–2667CrossRefGoogle Scholar
  21. 21.
    Vereyken EJ, Kraaij MD, Baan CC, Rezaee F, Weimar W, Wood KJ, Leenen PJ, Rowshani AT (2013) A shift towards pro-inflammatory CD16+ monocyte subsets with preserved cytokine production potential after kidney transplantation. PLoS One 8:e70152CrossRefGoogle Scholar
  22. 22.
    Der E, Ranabothu S, Suryawanshi H, Akat KM, Clancy R, Morozov P, Kustagi M, Czuppa M, Izmirly P, Belmont HM, Wang T, Jordan N, Bornkamp N, Nwaukoni J, Martinez J, Goilav B, Buyon JP, Tuschl T, Putterman C (2017) Single cell RNA sequencing to dissect the molecular heterogeneity in lupus nephritis. JCI Insight.  https://doi.org/10.1172/jci.insight.93009
  23. 23.
    Young MD, Mitchell TJ, Vieira Braga FA, Tran MGB, Stewart BJ, Ferdinand JR, Collord G, Botting RA, Popescu DM, Loudon KW, Vento-Tormo R, Stephenson E, Cagan A, Farndon SJ, Del Castillo Velasco-Herrera M, Guzzo C, Richoz N, Mamanova L, Aho T, Armitage JN, Riddick ACP, Mushtaq I, Farrell S, Rampling D, Nicholson J, Filby A, Burge J, Lisgo S, Maxwell PH, Lindsay S, Warren AY, Stewart GD, Sebire N, Coleman N, Haniffa M, Teichmann SA, Clatworthy M, Behjati S (2018) Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors. Science 361:594–599CrossRefGoogle Scholar
  24. 24.
    Lindstrom NO, De Sena Brandine G, Tran T, Ransick A, Suh G, Guo J, Kim AD, Parvez RK, Ruffins SW, Rutledge EA, Thornton ME, Grubbs B, McMahon JA, Smith AD, McMahon AP (2018) Progressive recruitment of mesenchymal progenitors reveals a time-dependent process of cell fate acquisition in mouse and human nephrogenesis. Dev Cell 45(651–660):e654Google Scholar
  25. 25.
    Lindstrom NO, Guo J, Kim AD, Tran T, Guo Q, De Sena Brandine G, Ransick A, Parvez RK, Thornton ME, Basking L, Grubbs B, McMahon JA, Smith AD, McMahon AP (2018) Conserved and divergent features of mesenchymal progenitor cell types within the cortical nephrogenic niche of the human and mouse kidney. J Am Soc Nephrol 29:806–824PubMedGoogle Scholar
  26. 26.
    Pode-Shakked N, Gershon R, Tam G, Omer D, Gnatek Y, Kanter I, Oriel S, Katz G, Harari-Steinberg O, Kalisky T, Dekel B (2017) Evidence of in vitro preservation of human nephrogenesis at the single-cell level. Stem Cell Reports 9:279–291CrossRefGoogle Scholar
  27. 27.
    Czerniecki SM, Cruz NM, Harder JL, Menon R, Annis J, Otto EA, Gulieva RE, Islas LV, Kim YK, Tran LM, Martins TJ, Pippin JW, Fu H, Kretzler M, Shankland SJ, Himmelfarb J, Moon RT, Paragas N, Freedman BS (2018) High-throughput screening enhances kidney organoid differentiation from human pluripotent stem cells and enables automated multidimensional phenotyping. Cell Stem Cell 22(929–940):e924Google Scholar
  28. 28.
    Morizane R, Bonventre JV (2017) Generation of nephron progenitor cells and kidney organoids from human pluripotent stem cells. Nat Protoc 12:195–207CrossRefGoogle Scholar
  29. 29.
    Takasato M, Er PX, Becroft M, Vanslambrouck JM, Stanley EG, Elefanty AG, Little MH (2014) Directing human embryonic stem cell differentiation towards a renal lineage generates a self-organizing kidney. Nat Cell Biol 16:118–126CrossRefGoogle Scholar
  30. 30.
    Taguchi A, Nishinakamura R (2017) Higher-order kidney organogenesis from pluripotent stem cells. Cell Stem Cell 21(730–746):e736Google Scholar
  31. 31.
    Adam M, Potter AS, Potter SS (2017) Psychrophilic proteases dramatically reduce single-cell RNA-seq artifacts: a molecular atlas of kidney development. Development 144:3625–3632CrossRefGoogle Scholar
  32. 32.
    Lake BB, Codeluppi S, Yung YC, Gao D, Chun J, Kharchenko PV, Linnarsson S, Zhang K (2017) A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA. Sci Rep 7:6031CrossRefGoogle Scholar
  33. 33.
    Ziegenhain C, Vieth B, Parekh S, Reinius B, Guillaumet-Adkins A, Smets M, Leonhardt H, Heyn H, Hellmann I, Enard W (2017) Comparative analysis of single-cell RNA sequencing methods. Mol Cell 65(631–643):e634Google Scholar
  34. 34.
    Buenrostro JD, Wu B, Litzenburger UM, Ruff D, Gonzales ML, Snyder MP, Chang HY, Greenleaf WJ (2015) Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523:486–490CrossRefGoogle Scholar
  35. 35.
    Stoeckius M, Hafemeister C, Stephenson W, Houck-Loomis B, Chattopadhyay PK, Swerdlow H, Satija R, Smibert P (2017) Simultaneous epitope and transcriptome measurement in single cells. Nat Methods 14:865–868CrossRefGoogle Scholar
  36. 36.
    Chappell L, Russell AJC, Voet T (2018) Single-cell (multi)omics technologies. Annu Rev Genomics Hum Genet 19:15–41CrossRefGoogle Scholar
  37. 37.
    Churchill W, Eade C (1943) The end of the beginning; war speeches. Little, Brown and Company, BostonGoogle Scholar

Copyright information

© IPNA 2019

Authors and Affiliations

  1. 1.Department of Pathology and ImmunologyWashington University in Saint Louis School of MedicineSt. LouisUSA
  2. 2.Division of Nephrology, Department of MedicineWashington University in Saint Louis School of MedicineSt. LouisUSA
  3. 3.Department of Developmental BiologyWashington University in Saint Louis School of MedicineSt. LouisUSA

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