The role of DNA methylation in chondrogenesis of human iPSCs as a stable marker of cartilage quality.
Humans
DNA Methylation
/ genetics
Induced Pluripotent Stem Cells
/ cytology
Chondrogenesis
/ genetics
Cartilage, Articular
/ cytology
Cell Differentiation
/ genetics
Epigenesis, Genetic
/ genetics
Chondrocytes
/ metabolism
Transcriptome
/ genetics
Fibroblasts
/ metabolism
CpG Islands
/ genetics
Cells, Cultured
Homeobox Protein Nkx-2.2
Methylation
Neo-cartilage
Regeneration
Transcriptional set points
hiPSCs
Journal
Clinical epigenetics
ISSN: 1868-7083
Titre abrégé: Clin Epigenetics
Pays: Germany
ID NLM: 101516977
Informations de publication
Date de publication:
15 Oct 2024
15 Oct 2024
Historique:
received:
11
03
2024
accepted:
07
10
2024
medline:
16
10
2024
pubmed:
16
10
2024
entrez:
15
10
2024
Statut:
epublish
Résumé
Lack of insight into factors that determine purity and quality of human iPSC (hiPSC)-derived neo-cartilage precludes applications of this powerful technology toward regenerative solutions in the clinical setting. Here, we set out to generate methylome-wide landscapes of hiPSC-derived neo-cartilages from different tissues-of-origin and integrated transcriptome-wide data to identify dissimilarities in set points of methylation with associated transcription and the respective pathways in which these genes act. We applied in vitro chondrogenesis using hiPSCs generated from two different tissue sources: skin fibroblasts and articular cartilage. Upon differentiation toward chondrocytes, these are referred to as hFiCs and hCiC, respectively. Genome-wide DNA methylation and RNA sequencing datasets were generated of the hiPSC-derived neo-cartilages, and the epigenetically regulated transcriptome was compared to that of neo-cartilage deposited by human primary articular cartilage (hPAC). Methylome-wide landscapes of neo-cartilages of hiPSCs reprogrammed from two different somatic tissues were 85% similar to that of hPACs. By integration of transcriptome-wide data, differences in transcriptionally active CpGs between hCiC relative to hPAC were prioritized. Among the CpG-gene pairs lower expressed in hCiCs relative to hPACs, we identified genes such as MGP, GDF5, and CHAD enriched in closely related pathways and involved in cartilage development that likely mark phenotypic differences in chondrocyte states. Vice versa, among the CpG-gene pairs higher expressed, we identified genes such as KIF1A or NKX2-2 enriched in neurogenic pathways and likely reflecting off target differentiation. We did not find significant variation between the neo-cartilages derived from hiPSCs of different tissue sources, suggesting that application of a robust differentiation protocol such as we applied here is more important as compared to the epigenetic memory of the cells of origin. Results of our study could be further exploited to improve quality, purity, and maturity of hiPSC-derived neo-cartilage matrix, ultimately to realize introduction of sustainable, hiPSC-derived neo-cartilage implantation into clinical practice.
Sections du résumé
BACKGROUND
BACKGROUND
Lack of insight into factors that determine purity and quality of human iPSC (hiPSC)-derived neo-cartilage precludes applications of this powerful technology toward regenerative solutions in the clinical setting. Here, we set out to generate methylome-wide landscapes of hiPSC-derived neo-cartilages from different tissues-of-origin and integrated transcriptome-wide data to identify dissimilarities in set points of methylation with associated transcription and the respective pathways in which these genes act.
METHODS
METHODS
We applied in vitro chondrogenesis using hiPSCs generated from two different tissue sources: skin fibroblasts and articular cartilage. Upon differentiation toward chondrocytes, these are referred to as hFiCs and hCiC, respectively. Genome-wide DNA methylation and RNA sequencing datasets were generated of the hiPSC-derived neo-cartilages, and the epigenetically regulated transcriptome was compared to that of neo-cartilage deposited by human primary articular cartilage (hPAC).
RESULTS
RESULTS
Methylome-wide landscapes of neo-cartilages of hiPSCs reprogrammed from two different somatic tissues were 85% similar to that of hPACs. By integration of transcriptome-wide data, differences in transcriptionally active CpGs between hCiC relative to hPAC were prioritized. Among the CpG-gene pairs lower expressed in hCiCs relative to hPACs, we identified genes such as MGP, GDF5, and CHAD enriched in closely related pathways and involved in cartilage development that likely mark phenotypic differences in chondrocyte states. Vice versa, among the CpG-gene pairs higher expressed, we identified genes such as KIF1A or NKX2-2 enriched in neurogenic pathways and likely reflecting off target differentiation.
CONCLUSIONS
CONCLUSIONS
We did not find significant variation between the neo-cartilages derived from hiPSCs of different tissue sources, suggesting that application of a robust differentiation protocol such as we applied here is more important as compared to the epigenetic memory of the cells of origin. Results of our study could be further exploited to improve quality, purity, and maturity of hiPSC-derived neo-cartilage matrix, ultimately to realize introduction of sustainable, hiPSC-derived neo-cartilage implantation into clinical practice.
Identifiants
pubmed: 39407288
doi: 10.1186/s13148-024-01759-y
pii: 10.1186/s13148-024-01759-y
doi:
Substances chimiques
Homeobox Protein Nkx-2.2
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
141Informations de copyright
© 2024. The Author(s).
Références
Goldring MB, Marcu KB. Cartilage homeostasis in health and rheumatic diseases. Arthritis Res Ther. 2009;11(3):224.
pubmed: 19519926
pmcid: 2714092
doi: 10.1186/ar2592
Woolf AD, Erwin J, March L. The need to address the burden of musculoskeletal conditions. Best Pract Res Clin Rheumatol. 2012;26(2):183–224.
pubmed: 22794094
doi: 10.1016/j.berh.2012.03.005
Tuan RS, Chen AF, Klatt BA. Cartilage regeneration. J Am Acad Orthop Surg. 2013;21(5):303–11.
pubmed: 23637149
pmcid: 4886741
doi: 10.5435/JAAOS-21-05-303
Kimura T, Yamashita A, Ozono K, Tsumaki N. Limited immunogenicity of human induced pluripotent stem cell-derived cartilages. Tissue Eng Part A. 2016;22(23–24):1367–75.
pubmed: 27762664
pmcid: 5175426
doi: 10.1089/ten.tea.2016.0189
Bomer N, Den HW, Suchiman H, Houtman E, Slieker RC, Heijmans BT, et al. Neo-cartilage engineered from primary chondrocytes is epigenetically similar to autologous cartilage, in contrast to using mesenchymal stem cells. Osteoarth Cartil. 2016;24(8):1423–30.
doi: 10.1016/j.joca.2016.03.009
Kamaraj A, Kyriacou H, Seah KTM, Khan WS. Use of human induced pluripotent stem cells for cartilage regeneration in vitro and within chondral defect models of knee joint cartilage in vivo: a preferred reporting items for systematic reviews and meta-analyses systematic literature review. Cytotherapy. 2021;23(8):647–61.
pubmed: 34059422
doi: 10.1016/j.jcyt.2021.03.008
Kretlow JD, Jin YQ, Liu W, Zhang WJ, Hong TH, Zhou G, et al. Donor age and cell passage affects differentiation potential of murine bone marrow-derived stem cells. BMC Cell Biol. 2008;9:60.
pubmed: 18957087
pmcid: 2584028
doi: 10.1186/1471-2121-9-60
Qu C, Puttonen KA, Lindeberg H, Ruponen M, Hovatta O, Koistinaho J, et al. Chondrogenic differentiation of human pluripotent stem cells in chondrocyte co-culture. Int J Biochem Cell Biol. 2013;45(8):1802–12.
pubmed: 23735325
doi: 10.1016/j.biocel.2013.05.029
Guha P, Morgan JW, Mostoslavsky G, Rodrigues NP, Boyd AS. Lack of immune response to differentiated cells derived from syngeneic induced pluripotent stem cells. Cell Stem Cell. 2013;12(4):407–12.
pubmed: 23352605
doi: 10.1016/j.stem.2013.01.006
Rodríguez Ruiz A, Dicks A, Tuerlings M, Schepers K, van Pel M, Nelissen R, et al. Cartilage from human-induced pluripotent stem cells: comparison with neo-cartilage from chondrocytes and bone marrow mesenchymal stromal cells. Cell Tissue Res. 2021;386:309–20.
pubmed: 34241697
pmcid: 8557148
doi: 10.1007/s00441-021-03498-5
Adkar SS, Wu C-L, Willard VP, Dicks A, Ettyreddy A, Steward N, et al. Step-wise chondrogenesis of human induced pluripotent stem cells and purification via a reporter allele generated by CRISPR-Cas9 genome editing. Stem Cells. 2019;37(1):65–76.
pubmed: 30378731
doi: 10.1002/stem.2931
Parry A, Rulands S, Reik W. Active turnover of DNA methylation during cell fate decisions. Nat Rev Genet. 2021;22(1):59–66.
pubmed: 33024290
doi: 10.1038/s41576-020-00287-8
Ziller MJ, Gu H, Müller F, Donaghey J, Tsai LT, Kohlbacher O, et al. Charting a dynamic DNA methylation landscape of the human genome. Nature. 2013;500(7463):477–81.
pubmed: 23925113
pmcid: 3821869
doi: 10.1038/nature12433
Doi A, Park IH, Wen B, Murakami P, Aryee MJ, Irizarry R, et al. Differential methylation of tissue- and cancer-specific CpG island shores distinguishes human induced pluripotent stem cells, embryonic stem cells and fibroblasts. Nat Genet. 2009;41(12):1350–3.
pubmed: 19881528
pmcid: 2958040
doi: 10.1038/ng.471
Kim K, Doi A, Wen B, Ng K, Zhao R, Cahan P, et al. Epigenetic memory in induced pluripotent stem cells. Nature. 2010;467(7313):285–90.
pubmed: 20644535
pmcid: 3150836
doi: 10.1038/nature09342
Lister R, Pelizzola M, Kida YS, Hawkins RD, Nery JR, Hon G, et al. Hotspots of aberrant epigenomic reprogramming in human induced pluripotent stem cells. Nature. 2011;471(7336):68–73.
pubmed: 21289626
pmcid: 3100360
doi: 10.1038/nature09798
Ohi Y, Qin H, Hong C, Blouin L, Polo JM, Guo T, et al. Incomplete DNA methylation underlies a transcriptional memory of somatic cells in human iPS cells. Nat Cell Biol. 2011;13(5):541–9.
pubmed: 21499256
pmcid: 3987913
doi: 10.1038/ncb2239
Dambrot C, van de Pas S, van Zijl L, Brändl B, Wang JW, Schalij MJ, et al. Polycistronic lentivirus induced pluripotent stem cells from skin biopsies after long term storage, blood outgrowth endothelial cells and cells from milk teeth. Differentiation. 2013;85(3):101–9.
pubmed: 23665895
doi: 10.1016/j.diff.2013.01.001
Tuerlings M, van Hoolwerff M, Houtman E, Suchiman E, Lakenberg N, Mei H, et al. RNA sequencing reveals interacting key determinants of osteoarthritis acting in subchondral bone and articular cartilage: identification of IL11 and CHADL as attractive treatment targets. Arthritis Rheumatol. 2021;73(5):789–99.
pubmed: 33258547
pmcid: 8252798
doi: 10.1002/art.41600
van Hoolwerff M, Rodriguez Ruiz A, Bouma M, Suchiman HED, Koning RI, Jost CR, et al. High-impact FN1 mutation decreases chondrogenic potential and affects cartilage deposition via decreased binding to collagen type II. Sci Adv. 2021;7(45):eabg8583.
pubmed: 34739320
pmcid: 8570604
doi: 10.1126/sciadv.abg8583
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15–21.
pubmed: 23104886
doi: 10.1093/bioinformatics/bts635
Anders S, Pyl PT, Huber W. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31(2):166–9.
pubmed: 25260700
doi: 10.1093/bioinformatics/btu638
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.
pubmed: 25516281
pmcid: 4302049
doi: 10.1186/s13059-014-0550-8
van Iterson M, Tobi EW, Slieker RC, den Hollander W, Luijk R, Slagboom PE, et al. MethylAid: visual and interactive quality control of large Illumina 450k datasets. Bioinformatics. 2014;30(23):3435–7.
pubmed: 25147358
doi: 10.1093/bioinformatics/btu566
Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics. 2014;30(10):1363–9.
pubmed: 24478339
pmcid: 4016708
doi: 10.1093/bioinformatics/btu049
Chen YA, Lemire M, Choufani S, Butcher DT, Grafodatskaya D, Zanke BW, et al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics. 2013;8(2):203–9.
pubmed: 23314698
pmcid: 3592906
doi: 10.4161/epi.23470
Martin-Trujillo A, Patel N, Richter F, Jadhav B, Garg P, Morton SU, et al. Rare genetic variation at transcription factor binding sites modulates local DNA methylation profiles. PLoS Genet. 2020;16(11):e1009189.
pubmed: 33216750
pmcid: 7679001
doi: 10.1371/journal.pgen.1009189
Fortin JP, Triche TJ Jr, Hansen KD. Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi. Bioinformatics. 2017;33(4):558–60.
pubmed: 28035024
doi: 10.1093/bioinformatics/btw691
Zhang D, Xue J, Peng F. The regulatory activities of MALAT1 in the development of bone and cartilage diseases. Front Endocrinol (Lausanne). 2022;13:1054827.
pubmed: 36452326
doi: 10.3389/fendo.2022.1054827
Boer CG, Hatzikotoulas K, Southam L, Stefánsdóttir L, Zhang Y, Coutinho de Almeida R, et al. Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations. Cell. 2021;184(18):4784–818.
pubmed: 34450027
pmcid: 8459317
doi: 10.1016/j.cell.2021.07.038
Coutinho de Almeida R, Mahfouz A, Mei H, Houtman E, den Hollander W, Soul J, et al. Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration. Rheumatology. 2020.
Coutinho de Almeida R, Ramos YFM, Mahfouz A, Den Hollander W, Lakenberg N, Houtman E, et al. RNA sequencing data integration reveals an miRNA interactome of osteoarthritis cartilage. Ann Rheum Dis. 2019;78(2):270–7.
pubmed: 30504444
doi: 10.1136/annrheumdis-2018-213882
Kilpinen H, Goncalves A, Leha A, Afzal V, Alasoo K, Ashford S, et al. Common genetic variation drives molecular heterogeneity in human iPSCs. Nature. 2017;546(7658):370–5.
pubmed: 28489815
pmcid: 5524171
doi: 10.1038/nature22403
Kim K, Zhao R, Doi A, Ng K, Unternaehrer J, Cahan P, et al. Donor cell type can influence the epigenome and differentiation potential of human induced pluripotent stem cells. Nat Biotechnol. 2011;29(12):1117–9.
pubmed: 22119740
pmcid: 3357310
doi: 10.1038/nbt.2052
Nishizawa M, Chonabayashi K, Nomura M, Tanaka A, Nakamura M, Inagaki A, et al. Epigenetic variation between human induced pluripotent stem cell lines is an indicator of differentiation capacity. Cell Stem Cell. 2016;19(3):341–54.
pubmed: 27476965
doi: 10.1016/j.stem.2016.06.019
Hessle L, Stordalen GA, Wenglén C, Petzold C, Tanner E, Brorson SH, et al. The skeletal phenotype of chondroadherin deficient mice. PLoS ONE. 2014;8(6):e63080.
pubmed: 23755099
doi: 10.1371/journal.pone.0063080
Akiyama H, Lyons JP, Mori-Akiyama Y, Yang X, Zhang R, Zhang Z, et al. Interactions between Sox9 and beta-catenin control chondrocyte differentiation. Genes Dev. 2004;18(9):1072–87.
pubmed: 15132997
pmcid: 406296
doi: 10.1101/gad.1171104
Luo G, D’Souza R, Hogue D, Karsenty G. The matrix Gla protein gene is a marker of the chondrogenesis cell lineage during mouse development. J Bone Miner Res. 1995;10(2):325–34.
pubmed: 7754814
doi: 10.1002/jbmr.5650100221
Houtman E, de Almeida RC, Tuerlings M, Suchiman E, Broekhuis D, Nelissen RGHH, et al. Characterization of dynamic changes in Matrix Gla Protein (MGP) gene expression as function of genetic risk alleles, osteoarthritis relevant stimuli, and the vitamin K inhibitor warfarin. Osteoarthr Cartil. 2021;29:1193–202.
doi: 10.1016/j.joca.2021.05.001
Boer CG, Szilagyi I, Nguyen NL, Neogi T, Meulenbelt I, Ikram MA, et al. Vitamin K antagonist anticoagulant usage is associated with increased incidence and progression of osteoarthritis. Ann Rheum Dis. 2021;80(5):598–604.
pubmed: 34412027
doi: 10.1136/annrheumdis-2020-219483
Xu H, Ding C, Guo C, Xiang S, Wang Y, Luo B, et al. Suppression of CRLF1 promotes the chondrogenic differentiation of bone marrow-derived mesenchymal stem and protects cartilage tissue from damage in osteoarthritis via activation of miR-320. Mol Med. 2021;27(1):116.
pubmed: 34551709
pmcid: 8456664
doi: 10.1186/s10020-021-00369-1
Rodríguez Ruiz A, Tuerlings M, Das A, Coutinho de Almeida R, Suchiman HED, Nelissen R, et al. The role of TNFRSF11B in development of osteoarthritic cartilage. Rheumatology (Oxford). 2022;61(2):856–64.
pubmed: 33989379
doi: 10.1093/rheumatology/keab440
Wu CL, Dicks A, Steward N, Tang R, Katz DB, Choi YR, et al. Single cell transcriptomic analysis of human pluripotent stem cell chondrogenesis. Nat Commun. 2021;12(1):362.
pubmed: 33441552
pmcid: 7806634
doi: 10.1038/s41467-020-20598-y