Tubular cell and keratinocyte single-cell transcriptomics applied to lupus nephritis reveal type I IFN and fibrosis relevant pathways.
Biopsy
Cell Lineage
/ genetics
Computational Biology
/ methods
Extracellular Matrix Proteins
/ genetics
Fibrosis
Gene Expression Profiling
/ methods
Humans
Interferon Type I
/ metabolism
Keratinocytes
/ metabolism
Kidney Tubules
/ cytology
Lupus Nephritis
/ genetics
Protein Binding
Signal Transduction
Single-Cell Analysis
Skin
/ immunology
Transcriptome
Journal
Nature immunology
ISSN: 1529-2916
Titre abrégé: Nat Immunol
Pays: United States
ID NLM: 100941354
Informations de publication
Date de publication:
07 2019
07 2019
Historique:
received:
18
04
2018
accepted:
26
03
2019
pubmed:
22
5
2019
medline:
10
7
2019
entrez:
22
5
2019
Statut:
ppublish
Résumé
The molecular and cellular processes that lead to renal damage and to the heterogeneity of lupus nephritis (LN) are not well understood. We applied single-cell RNA sequencing (scRNA-seq) to renal biopsies from patients with LN and evaluated skin biopsies as a potential source of diagnostic and prognostic markers of renal disease. Type I interferon (IFN)-response signatures in tubular cells and keratinocytes distinguished patients with LN from healthy control subjects. Moreover, a high IFN-response signature and fibrotic signature in tubular cells were each associated with failure to respond to treatment. Analysis of tubular cells from patients with proliferative, membranous and mixed LN indicated pathways relevant to inflammation and fibrosis, which offer insight into their histologic differences. In summary, we applied scRNA-seq to LN to deconstruct its heterogeneity and identify novel targets for personalized approaches to therapy.
Identifiants
pubmed: 31110316
doi: 10.1038/s41590-019-0386-1
pii: 10.1038/s41590-019-0386-1
pmc: PMC6584054
mid: NIHMS1525648
doi:
Substances chimiques
Extracellular Matrix Proteins
0
Interferon Type I
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
915-927Subventions
Organisme : NIAMS NIH HHS
ID : UH2 AR067685
Pays : United States
Organisme : NIAMS NIH HHS
ID : UM2 AR067678
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR003167
Pays : United States
Organisme : NHGRI NIH HHS
ID : T32 HG002295
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067681
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067689
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067690
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067694
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067679
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067688
Pays : United States
Organisme : NIAMS NIH HHS
ID : F31 AR070582
Pays : United States
Organisme : NHGRI NIH HHS
ID : U01 HG009379
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067677
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067676
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067691
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000371
Pays : United States
Investigateurs
Jennifer Anolik
(J)
William Apruzzese
(W)
Arnon Arazi
(A)
Celine Berthier
(C)
Michael Brenner
(M)
Jill Buyon
(J)
Robert Clancy
(R)
Sean Connery
(S)
Melissa Cunningham
(M)
Maria Dall'Era
(M)
Anne Davidson
(A)
Evan Der
(E)
Andrea Fava
(A)
Chamith Fonseka
(C)
Richard Furie
(R)
Dan Goldman
(D)
Rohit Gupta
(R)
Joel Guthridge
(J)
Nir Hacohen
(N)
David Hildeman
(D)
Paul Hoover
(P)
Raymond Hsu
(R)
Judith James
(J)
Ruba Kado
(R)
Kenneth Kalunian
(K)
Diane Kamen
(D)
Mattias Kretzler
(M)
Holden Maecker
(H)
Elena Massarotti
(E)
William McCune
(W)
Maureen McMahon
(M)
Meyeon Park
(M)
Fernanda Payan-Schober
(F)
William Pendergraft
(W)
Michelle Petri
(M)
Mina Pichavant
(M)
Chaim Putterman
(C)
Deepak Rao
(D)
Soumya Raychaudhuri
(S)
Kamil Slowikowski
(K)
Hemant Suryawanshi
(H)
Thomas Tuschl
(T)
Paul Utz
(P)
Dia Waguespack
(D)
David Wofsy
(D)
Fan Zhang
(F)
Commentaires et corrections
Type : CommentIn
Type : CommentIn
Type : ErratumIn
Références
Tsokos, G. C. Systemic lupus erythematosus. N. Engl. J. Med. 365, 2110–2121 (2011).
doi: 10.1056/NEJMra1100359
Mohan, C. & Putterman, C. Genetics and pathogenesis of systemic lupus erythematosus and lupus nephritis. Nat. Rev. Nephrol. 11, 329–341 (2015).
doi: 10.1038/nrneph.2015.33
Weening, J. J. et al. The classification of glomerulonephritis in systemic lupus erythematosus revisited. J. Am. Soc. Nephrol. 15, 241–250 (2004).
doi: 10.1097/01.ASN.0000108969.21691.5D
Yu, F. et al. Tubulointerstitial lesions of patients with lupus nephritis classified by the 2003 international society of nephrology and renal pathology society system. Kidney Int. 77, 820–829 (2010).
doi: 10.1038/ki.2010.13
Hsieh, C. et al. Predicting outcomes of lupus nephritis with tubulointerstitial inflammation and scarring. Arthritis Care Res. 63, 865–874 (2011).
doi: 10.1002/acr.20441
Alsuwaida, A. O. Interstitial inflammation and long-term renal outcomes in lupus nephritis. Lupus 22, 1446–1454 (2013).
doi: 10.1177/0961203313507986
Misra, R. & Gupta, R. Biomarkers in lupus nephritis. Int. J. Rheum. Dis. 18, 219–232 (2015).
doi: 10.1111/1756-185X.12602
Reich, A., Marcinow, K. & Bialynicki-Birula, R. The lupus band test in systemic lupus erythematosus patients. Ther. Clin. Risk Manag. 7, 27–32 (2011).
doi: 10.2147/TCRM.S10145
Der, E. et al. Single cell RNA sequencing to dissect the molecular heterogeneity in lupus nephritis. JCI Insight 2(9), e93009 (2017).
Ofengeim, D., Giagtzoglou, N., Huh, D., Zou, C. & Yuan, J. Single-cell RNA sequencing: unraveling the brain one cell at a time. Trends Mol. Med. 23, 563–576 (2017).
doi: 10.1016/j.molmed.2017.04.006
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33, 495–502 (2015).
doi: 10.1038/nbt.3192
Kim, K.-T. et al. Application of single-cell RNA sequencing in optimizing a combinatorial therapeutic strategy in metastatic renal cell carcinoma. Genome Biol. 17, 80 (2016).
doi: 10.1186/s13059-016-0945-9
Young, M. D. et al. Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors. Science 361, 594–599 (2018).
doi: 10.1126/science.aat1699
Park, J. et al. Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease. Science 360, eaar2131 (2018).
Schittek, B. et al. Dermcidin: a novel human antibiotic peptide secreted by sweat glands. Nat. Immunol. 2, 1133–1137 (2001).
doi: 10.1038/ni732
Du, J. et al. MLANA/MART1 and SILV/PMEL17/GP100 are transcriptionally regulated by mitf in melanocytes and melanoma. Am. J. Pathol. 163, 333–343 (2003).
doi: 10.1016/S0002-9440(10)63657-7
Elkon, K. B. & Stone, V. V. Type I interferon and systemic lupus erythematosus. J. Interferon Cytokine Res. 31, 803–812 (2011).
doi: 10.1089/jir.2011.0045
Lan, H. Y. Tubular epithelial-myofibroblast transdifferentiation mechanisms in proximal tubule cells. Curr. Opin. Nephrol. Hypertens. 12, 25–29 (2003).
doi: 10.1097/00041552-200301000-00005
Ng, Y. Y. et al. Tubular epithelial-myofibroblast transdifferentiation in progressive tubulointerstitial fibrosis in 5/6 nephrectomized rats. Kidney Int. 54, 864–876 (1998).
doi: 10.1046/j.1523-1755.1998.00076.x
Lamouille, S., Xu, J. & Derynck, R. Molecular mechanisms of epithelial–mesenchymal transition. Nat. Rev. Mol. Cell Biol. 15, 178–196 (2014).
doi: 10.1038/nrm3758
Wolf, G. & Ziyadeh, F. N. Renal tubular hypertrophy induced by angiotensin II. Semin. Nephrol. 17, 448–454 (1997).
pubmed: 9316213
Zhang, X. et al. TIMP-1 promotes age-related renal fibrosis through upregulating ICAM-1 in human TIMP-1 transgenic mice. J. Gerontol. A Biol. Sci. Med. Sci. 61, 1130–1143 (2006).
doi: 10.1093/gerona/61.11.1130
Ling, X. B. et al. Integrative urinary peptidomics in renal transplantation identifies biomarkers for acute rejection. J. Am. Soc. Nephrol. 21, 646–653 (2010).
doi: 10.1681/ASN.2009080876
Su, Z. et al. Excessive activation of the alternative complement pathway in autosomal dominant polycystic kidney disease. J. Intern. Med. 276, 470–485 (2014).
doi: 10.1111/joim.12214
Parikh, S. V. et al. Molecular imaging of the kidney in lupus nephritis to characterize response to treatment. Transl. Res. 182, 1–13 (2017).
doi: 10.1016/j.trsl.2016.10.010
Strutz, F. et al. Basic fibroblast growth factor expression is increased in human renal fibrogenesis and may mediate autocrine fibroblast proliferation. Kidney Int. 57, 1521–1538 (2000).
doi: 10.1046/j.1523-1755.2000.00997.x
Smith, E. R., Tan, S.-J., Holt, S. G. & Hewitson, T. D. FGF23 is synthesised locally by renal tubules and activates injury-primed fibroblasts. Sci. Rep. 7, 3345 (2017).
doi: 10.1038/s41598-017-02709-w
Meran, S. & Steadman, R. Fibroblasts and myofibroblasts in renal fibrosis. Int. J. Exp. Pathol. 92, 158–167 (2011).
doi: 10.1111/j.1365-2613.2011.00764.x
Yang, J. & Liu, Y. Dissection of key events in tubular epithelial to myofibroblast transition and its implications in renal interstitial fibrosis. Am. J. Pathol. 159, 1465–1475 (2001).
doi: 10.1016/S0002-9440(10)62533-3
Yang, J. & Liu, Y. Blockage of tubular epithelial to myofibroblast transition by hepatocyte growth factor prevents renal interstitial fibrosis. J. Am. Soc. Nephrol. 13, 96–107 (2002).
pubmed: 11752026
Castellano, G. et al. Local synthesis of interferon-alpha in lupus nephritis is associated with type I interferons signature and LMP7 induction in renal tubular epithelial cells. Arthritis Res. Ther. 17, 72 (2015).
doi: 10.1186/s13075-015-0588-3
Stephenson, W. et al. Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation. Nat. Commun. 9, 791 (2018).
doi: 10.1038/s41467-017-02659-x
MacParland, S. A. et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat. Commun. 9, 4383 (2018).
doi: 10.1038/s41467-018-06318-7
Vento-Tormo, R. et al. Single-cell reconstruction of the early maternal–fetal interface in humans. Nature 563, 347 (2018).
doi: 10.1038/s41586-018-0698-6
Austin, H. A., Boumpas, D. T., Vaughan, E. M. & Balow, J. E. Predicting renal outcomes in severe lupus nephritis: contributions of clinical and histologic data. Kidney Int. 45, 544–550 (1994).
doi: 10.1038/ki.1994.70
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10–12 (2011).
doi: 10.14806/ej.17.1.200
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).
doi: 10.1093/bioinformatics/btt656
Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
doi: 10.1016/j.cell.2015.05.002
Pavličev, M. et al. Single-cell transcriptomics of the human placenta: inferring the cell communication network of the maternal–fetal interface. Genome Res. 27, 349–361 (2017).
doi: 10.1101/gr.207597.116
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
doi: 10.1186/s13059-014-0550-8
Kuleshov, M. V. et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44, W90–W97 (2016).
doi: 10.1093/nar/gkw377
Chen, E. Y. et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128 (2013).
doi: 10.1186/1471-2105-14-128
Croft, D. et al. The Reactome pathway knowledgebase. Nucleic Acids Res. 42, D472–D477 (2014).
doi: 10.1093/nar/gkt1102
Fabregat, A. et al. The reactome pathway knowledgebase. Nucleic Acids Res. 46, D649–D655 (2018).
doi: 10.1093/nar/gkx1132
Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000).
doi: 10.1093/nar/28.1.27
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. & Morishima, K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353–D361 (2017).
doi: 10.1093/nar/gkw1092
Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M. & Tanabe, M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 44, D457–D462 (2016).
doi: 10.1093/nar/gkv1070