Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Bioprinted 3D outer retina barrier uncovers RPE-dependent choroidal phenotype in advanced macular degeneration

Nature Methods volume 20, pages 149–161 (2023)Cite this article

Subjects

Abstract

Age-related macular degeneration (AMD), a leading cause of blindness, initiates in the outer-blood-retina-barrier (oBRB) formed by the retinal pigment epithelium (RPE), Bruch’s membrane, and choriocapillaris. The mechanisms of AMD initiation and progression remain poorly understood owing to the lack of physiologically relevant human oBRB models. To this end, we engineered a native-like three-dimensional (3D) oBRB tissue (3D-oBRB) by bioprinting endothelial cells, pericytes, and fibroblasts on the basal side of a biodegradable scaffold and establishing an RPE monolayer on top. In this 3D-oBRB model, a fully-polarized RPE monolayer provides barrier resistance, induces choriocapillaris fenestration, and supports the formation of Bruch’s-membrane-like structure by inducing changes in gene expression in cells of the choroid. Complement activation in the 3D-oBRB triggers dry AMD phenotypes (including subRPE lipid-rich deposits called drusen and choriocapillaris degeneration), and HIF-α stabilization or STAT3 overactivation induce choriocapillaris neovascularization and type-I wet AMD phenotype. The 3D-oBRB provides a physiologically relevant model to studying RPE–choriocapillaris interactions under healthy and diseased conditions.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Design of 3D-oBRB.
Fig. 2: Engineering of 3D-oBRB.
Fig. 3: Capillary maturation in 3D-oBRB.
Fig. 4: RPE maturity in 3D-oBRB.
Fig. 5: RPE-dependent choroid degeneration in dry and wet AMD models of 3D-oBRB.
Fig. 6: Bevacizumab treatment suppresses wet AMD in 3D-oBRB.

Similar content being viewed by others

Data availability

The scRNA-seq data generated in this study have been deposited in the Gene Expression Omnibus database under accession code GSE214928. These RNA-seq data are openly available without any restriction. All the processed data are available within the article. All the raw data generated in this study are provided in Source Data files. Source data for Fig. 6 are available in a figshare repository at https://doi.org/10.6084/m9.figshare.21300198. Source data are provided with this paper.

Code availability

Angiogenesis quantification was performed on MATLAB version 2019b (Mathworks). The custom MATLAB code is available in Supplementary Information.

References

  1. Wong, W. L. et al. Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis. Lancet Glob. Health 2, e106–e116 (2014).

    Article  Google Scholar 

  2. Song, M. J. & Bharti, K. Looking into the future: using induced pluripotent stem cells to build two and three dimensional ocular tissue for cell therapy and disease modeling. Brain Res. 1638, 2–14 (2016).

    Article  CAS  Google Scholar 

  3. McLeod, D. S. et al. Relationship between RPE and choriocapillaris in age-related macular degeneration. Invest. Ophthalmol. Vis. Sci. 50, 4982–4991 (2009).

    Article  Google Scholar 

  4. Bhutto, I. & Lutty, G. Understanding age-related macular degeneration (AMD): relationships between the photoreceptor/retinal pigment epithelium/Bruch’s membrane/choriocapillaris complex. Mol. Asp. Med 33, 295–317 (2012).

    Article  CAS  Google Scholar 

  5. Farecki, M. L. et al. Characteristics of type 1 and 2 CNV in exudative AMD in OCT-angiography. Graefes Arch. Clin. Exp. Ophthalmol. 255, 913–921 (2017).

    Article  Google Scholar 

  6. Kovach, J. L., Schwartz, S. G., Flynn, H. W. Jr. & Scott, I. U. Anti-VEGF treatment strategies for wet AMD. J. Ophthalmol. 2012, 786870 (2012).

    Article  Google Scholar 

  7. Barben, M., Samardzija, M. & Grimm, C. The role of hypoxia, hypoxia-inducible factor (HIF), and VEGF in retinal angiomatous proliferation. Adv. Exp. Med Biol. 1074, 177–183 (2018).

    Article  CAS  Google Scholar 

  8. Manian, K. V. et al. 3D iPSC modeling of the retinal pigment epithelium–choriocapillaris complex identifies factors involved in the pathology of macular degeneration. Cell Stem Cell 28, 978 (2021).

    Article  CAS  Google Scholar 

  9. Benedicto, I. et al. Concerted regulation of retinal pigment epithelium basement membrane and barrier function by angiocrine factors. Nat. Commun. 8, 15374 (2017).

    Article  CAS  Google Scholar 

  10. Chirco, K. R., Sohn, E. H., Stone, E. M., Tucker, B. A. & Mullins, R. F. Structural and molecular changes in the aging choroid: implications for age-related macular degeneration. Eye (Lond.) 31, 10–25 (2017).

    Article  CAS  Google Scholar 

  11. Sweeney, M. & Foldes, G. It takes two: endothelial-perivascular cell cross-talk in vascular development and disease. Front Cardiovasc Med 5, 154 (2018).

    Article  CAS  Google Scholar 

  12. Campbell, M. & Humphries, P. The blood-retina barrier: tight junctions and barrier modulation. Adv. Exp. Med Biol. 763, 70–84 (2012).

    Article  CAS  Google Scholar 

  13. Nickla, D. L. & Wallman, J. The multifunctional choroid. Prog. Retin Eye Res 29, 144–168 (2010).

    Article  Google Scholar 

  14. Hoshino, A., Chiba, H., Nagai, K., Ishii, G. & Ochiai, A. Human vascular adventitial fibroblasts contain mesenchymal stem/progenitor cells. Biochem. Biophys. Res. Commun. 368, 305–310 (2008).

    Article  CAS  Google Scholar 

  15. Orlova, V. V. et al. Generation, expansion and functional analysis of endothelial cells and pericytes derived from human pluripotent stem cells. Nat. Protoc. 9, 1514–1531 (2014).

    Article  CAS  Google Scholar 

  16. Sharma, R. et al. Clinical-grade stem cell-derived retinal pigment epithelium patch rescues retinal degeneration in rodents and pigs Sci. Transl. Med. 11, eaat5580 (2019).

  17. Shiihara, H. et al. Quantitative analyses of diameter and running pattern of choroidal vessels in central serous chorioretinopathy by en face images. Sci. Rep. 10, 9591 (2020).

    Article  Google Scholar 

  18. Royston, D. Preventing the inflammatory response to open-heart surgery: the role of aprotinin and other protease inhibitors. Int. J. Cardiol. 53, S11–S37 (1996).

    Article  Google Scholar 

  19. Baltazar, T. et al. Three dimensional bioprinting of a vascularized and perfusable skin graft using human keratinocytes, fibroblasts, pericytes, and endothelial cells. Tissue Eng. Part A 26, 227–238 (2020).

    Article  CAS  Google Scholar 

  20. Guillotin, B. et al. Laser assisted bioprinting of engineered tissue with high cell density and microscale organization. Biomaterials 31, 7250–7256 (2010).

    Article  CAS  Google Scholar 

  21. Abdeen, A. A., Lee, J., Mo, S. H. & Kilian, K. A. Spatially defined stem cell-laden hydrogel islands for directing endothelial tubulogenesis. J. Mater. Chem. B 3, 7896–7898 (2015).

    Article  CAS  Google Scholar 

  22. Lamalice, L., Le Boeuf, F. & Huot, J. Endothelial cell migration during angiogenesis. Circ. Res. 100, 782–794 (2007).

    Article  CAS  Google Scholar 

  23. Brindle, N. P., Saharinen, P. & Alitalo, K. Signaling and functions of angiopoietin-1 in vascular protection. Circ. Res. 98, 1014–1023 (2006).

    Article  CAS  Google Scholar 

  24. Newman, A. C., Nakatsu, M. N., Chou, W., Gershon, P. D. & Hughes, C. C. The requirement for fibroblasts in angiogenesis: fibroblast-derived matrix proteins are essential for endothelial cell lumen formation. Mol. Biol. Cell 22, 3791–3800 (2011).

    Article  CAS  Google Scholar 

  25. Payne, L. B. et al. The pericyte microenvironment during vascular development. Microcirculation 26, e12554 (2019).

    Article  Google Scholar 

  26. Maminishkis, A. et al. Confluent monolayers of cultured human fetal retinal pigment epithelium exhibit morphology and physiology of native tissue. Invest. Ophthalmol. Vis. Sci. 47, 3612–3624 (2006).

    Article  Google Scholar 

  27. Campochiaro, P. A., Jerdon, J. A. & Glaser, B. M. The extracellular matrix of human retinal pigment epithelial cells in vivo and its synthesis in vitro. Invest. Ophthalmol. Vis. Sci. 27, 1615–1621 (1986).

    CAS  Google Scholar 

  28. Choi, W. et al. Choriocapillaris and choroidal microvasculature imaging with ultrahigh speed OCT angiography. PLoS One 8, e81499 (2013).

    Article  Google Scholar 

  29. Grebe, R. et al. Ultrastructural analysis of submacular choriocapillaris and its transport systems in AMD and aged control eyes. Exp. Eye Res 181, 252–262 (2019).

    Article  CAS  Google Scholar 

  30. Takei, Y. & Ozanics, V. Origin and development of Bruch’s membrane in monkey fetuses: an electron microscopic study. Invest Ophthalmol. 14, 903–916 (1975).

    CAS  Google Scholar 

  31. Voigt, A. P. et al. Choroidal endothelial and macrophage gene expression in atrophic and neovascular macular degeneration. Hum. Mol. Genet 31, 2406–2423 (2022).

    Article  CAS  Google Scholar 

  32. Kosyakova, N. et al. Differential functional roles of fibroblasts and pericytes in the formation of tissue-engineered microvascular networks in vitro. NPJ Regen. Med 5, 1 (2020).

    Article  CAS  Google Scholar 

  33. Curcio, C. J. in Retina Vol. 1 (eds Ryan, S. J.) Ch. 20 (Elsevier, 2013).

  34. Johnson, L. V. et al. Cell culture model that mimics drusen formation and triggers complement activation associated with age-related macular degeneration. Proc. Natl Acad. Sci. USA 108, 18277–18282 (2011).

    Article  CAS  Google Scholar 

  35. Galloway, C. A. et al. Drusen in patient-derived hiPSC-RPE models of macular dystrophies. Proc. Natl Acad. Sci. USA 114, E8214–E8223 (2017).

    Article  CAS  Google Scholar 

  36. Sharma, R. et al. Epithelial phenotype restoring drugs suppress macular degeneration phenotypes in an iPSC model. Nat. Commun. 12, 7293 (2021).

    Article  CAS  Google Scholar 

  37. Vadlapatla, R. K., Vadlapudi, A. D. & Mitra, A. K. Hypoxia-inducible factor-1 (HIF-1): a potential target for intervention in ocular neovascular diseases. Curr. Drug Targets 14, 919–935 (2013).

    Article  CAS  Google Scholar 

  38. Mammadzada, P., Corredoira, P. M. & Andre, H. The role of hypoxia-inducible factors in neovascular age-related macular degeneration: a gene therapy perspective. Cell. Mol. Life Sci. 77, 819–833 (2020).

    Article  CAS  Google Scholar 

  39. Theriault, J. R. et al. Discovery of a new molecular probe ML228: an activator of the hypoxia inducible factor (HIF) pathway. Bioorg. Med. Chem. Lett. 22, 76–81 (2012).

    Article  CAS  Google Scholar 

  40. Yang, J. et al. Two-year risk of exudation in eyes with nonexudative age-related macular degeneration and subclinical neovascularization detected with swept source optical coherence tomography angiography. Am. J. Ophthalmol. 208, 1–11 (2019).

    Article  Google Scholar 

  41. Li, X. et al. Hyperglycaemia exacerbates choroidal neovascularisation in mice via the oxidative stress-induced activation of STAT3 signalling in RPE cells. PLoS ONE 7, e47600 (2012).

    Article  CAS  Google Scholar 

  42. Jing Wang, Q. B., et al. Chrysin alleviates DNA damage to improve disturbed immuno-homeostasis and pro-angiogenic environment in laser-induced choroidal neovascularization. Preprint available at Research Square https://doi.org/10.21203/rs.3.rs-827729/v1 (2021).

  43. Wavre-Shapton, S. T., Tolmachova, T., Lopes da Silva, M., Futter, C. E. & Seabra, M. C. Conditional ablation of the choroideremia gene causes age-related changes in mouse retinal pigment epithelium. PLoS One 8, e57769 (2013).

    Article  CAS  Google Scholar 

  44. Booij, J. C., Baas, D. C., Beisekeeva, J., Gorgels, T. G. & Bergen, A. A. The dynamic nature of Bruch’s membrane. Prog. Retin. Eye Res. 29, 1–18 (2010).

    Article  CAS  Google Scholar 

  45. Huang, J. D., Presley, J. B., Chimento, M. F., Curcio, C. A. & Johnson, M. Age-related changes in human macular Bruch’s membrane as seen by quick-freeze/deep-etch. Exp. Eye Res. 85, 202–218 (2007).

    Article  CAS  Google Scholar 

  46. Farazdaghi, M. K. & Ebrahimi, K. B. Role of the choroid in age-related macular degeneration: a current review. J. Ophthalmic Vis. Res 14, 78–87 (2019).

    Article  Google Scholar 

  47. Cavallotti, C., Artico, M., Pescosolido, N., Leali, F. M. & Feher, J. Age-related changes in the human retina. Can. J. Ophthalmol. 39, 61–68 (2004).

    Article  Google Scholar 

  48. Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 e1821 (2019).

    Article  CAS  Google Scholar 

  49. Zhou, W. et al. Single-cell analysis reveals regulatory gene expression dynamics leading to lineage commitment in early T cell development. Cell Syst. 9, 321–337 (2019).

    Article  CAS  Google Scholar 

  50. Chen, E. Y. et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinf. 14, 128 (2013).

    Article  Google Scholar 

  51. Kuleshov, M. V. et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44, W90–W97 (2016).

    Article  CAS  Google Scholar 

  52. Xie, Z. et al. Gene set knowledge discovery with Enrichr. Curr. Protoc. 1, e90 (2021).

    Article  CAS  Google Scholar 

  53. Cowan, C. S. et al. Cell types of the human retina and its organoids at single-cell resolution. Cell 182, 1623–1640 (2020).

    Article  CAS  Google Scholar 

  54. Song, H. W. et al. Transcriptomic comparison of human and mouse brain microvessels. Sci. Rep. 10, 12358 (2020).

    Article  CAS  Google Scholar 

  55. McGinnis, C. S., Murrow, L. M. & Gartner, Z. J. DoubletFinder: doublet detection in single-cell RNA sequencing data using artificial nearest neighbors. Cell Syst. 8, 329–337 (2019).

    Article  CAS  Google Scholar 

  56. Safran, M. et al. in Practical Guide to Life Science Databases (eds Abugessaisa, I. & Kasukawa, T.) 27–56 (Springer Nature, 2021).

Download references

Acknowledgements

The authors thank R. Fariss, NEI Biological Imaging Core, M. Abu from NEI histology core for processing the samples for TEM and taking images, D. McGaughey OGVFB, NEI for advice on scRNA-seq data analysis. This work was supported by funds from the NEI Intramural Research Program to K.B., NCATS intramural funds to M.J.S., M.F., and I.S., NHLBI intramural funds to M.B., Department of Defense grant (grant number 11831456) to M.J.S. and K.B., and Cures Acceleration Network program to M.J.S. and M.F.

Author information

Author notes

  1. These authors contributed equally: Russ Quinn, Eric Nguyen.

Authors and Affiliations

  1. National Eye Institute, National Institutes of Health, Bethesda, USA

    Min Jae Song, Russ Quinn, Eric Nguyen, Christopher Hampton, Ruchi Sharma, Tea Soon Park, Roba Dejene, Devika Bose, Francesca Barone, Arvydas Maminishkis & Kapil Bharti

  2. National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, USA

    Min Jae Song, Ty Voss, Carlos Tristan, Claire Weber, Anju Singh, Yu-Chi Chen, Paige Derr, Kristy Derr, Sam Michael, Ilyas Singec, Marc Ferrer & Kapil Bharti

  3. Department of Human Genetics Amsterdam, Section of Ophthalmogenetics, Amsterdam University Medical Centers (AUMC), University of Amsterdam, Amsterdam, The Netherlands

    Céline Koster

  4. National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA

    Guibin Chen & Manfred Boehm

Authors
  1. Min Jae Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Russ Quinn
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eric Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Christopher Hampton
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ruchi Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tea Soon Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Céline Koster
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ty Voss
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Carlos Tristan
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Claire Weber
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Anju Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Roba Dejene
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Devika Bose
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Yu-Chi Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Paige Derr
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Kristy Derr
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Sam Michael
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Francesca Barone
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Guibin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Manfred Boehm
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Arvydas Maminishkis
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Ilyas Singec
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Marc Ferrer
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Kapil Bharti
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: K.B., M.J.S, and M.F.; methodology: K.B., R.Q., E.N, M.J.S, T.V., I.S., and M.F.; Investigation: R.Q., E.N, M.J.S, C.H., R.S., T.S.P., C.K., C.T., C.W., A.S., R.D., D.B., P.D., K.D., S.M., G. C., M.B., A.M., and F.B.; analysis: Y.-C.C., K.B., R.Q., E.N, and M.J.S.; project administration: R.Q., E.N, and M.J.S; writing, review, and editing: K.B., E.N, M.J.S, and M.F; funding acquisition: K.B. M.F., M.B., I.S., and M.J.S.; resources: K.B. and M.F.; supervision: K.B. and M.F.

Corresponding author

Correspondence to Kapil Bharti.

Ethics declarations

Competing interests

The authors have an approved patent on this technology in Australia (#AU2017359330B2) and a pending patent in the US (#US20190290803A1).

Peer review

Peer review information

Nature Methods thanks Reinhold Medina, Botond Roska, Ruchira Singh for their contribution to the peer review of this work. Primary Handling Editor: Madhura Mukhopadhyay, in collaboration with the Nature Methods team.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Pericytes colocalize to capillaries.

a-c, Pericytes immunostained with NG2 (a, green), α-SMA (b, green), and PDGFR-β (c, green) and ECs immunostained with CD31 (magenta). (n = 3), scale bars, 30 μm.

Extended Data Fig. 2 ECs, pericytes, and fibroblast are essential for formation of dense and stable capillary-bed.

a, b, EC only bioink; c, d, EC + pericyte bioink; e, f, EC + fibroblasts bioink; g, h, EC + pericyte + fibroblasts bioink 7 days (a, c, e, g) and 10 days (b, d, f, h) after bioprinting. Tissues fixed at analyzed for GFP expression (green) (n = 4). Scale bars, 500 μm.

Extended Data Fig. 3 Time course of fenestration marker expression in 3D-oBRB.

a-d, 3D vascular growth within tissues fixed at week 1 (a), week 2 (b), week 3 (c), and week 4 (d). Tissues were immunostained with FELS (green) and CD31 (magenta). Scale bars, 50 μm. n = 3.

Extended Data Fig. 4 ECM protein expressions in 3D-oBRB.

a-f, 3D reconstructed images of tissues immunostained for CD31 (magenta, a-f), nuclei (blue, a-f), LAMININ (LMN, green a, b), ELASTIN (ELN, green, c, d), COLLAGEN IV (COL IV, green, e, f), viewed at the subRPE level (a, c, e) and choriocapillaris level (b, d, f). N = 3. g, cross section of 3D-oBRB immunostained for Bruch’s membrane proteins LAMININ (yellow) and COLLAGEN IV (COL IV, magenta). Nuclei stained with DAPI (cyan). N = 3. Scale bar, 10μm.

Extended Data Fig. 5 Time course study of dry AMD phenotype induction in 3D-oBRB.

a-l, Nile red (yellow), anti-CD31 (magenta), and Hoechst (nucleus, blue) stained en face images of RPE (a-f), RPE-proximal choriocapillaris (g-l), and RPE-distal choriocapillaris (m-r) from 3D-oBRB treated with complement incompetent human serum (CI-HS, a, c, e, g, i, k, m, o, q) complement competent human serum (CC-HS, b, d, f, h, j, l, n, p, r) for 2, 4, and 7 days. Scale bars, 60 μm (a-l), 300 μm (m-r) n = 3. s-x, Nile red (yellow), anti-CD31 (magenta), and Hoechst (nucleus, blue) stained lateral view 3D rendered images of 3D-oBRB, treated with CI-HS (s, u, w) or CC-HS (t, v, x).

Extended Data Fig. 6 ML228 treatment on 2D-iRPE and 3D-oBRB.

a-f, RPE monoculture at 48 hr (a,d), 96 hr (b,e), and 2 weeks (c,f) from the beginning of ML228 (2 µM; 96 hr) treatment, immunostained with HIF-1α (magenta), ZO-1 (green), and Hoeschst (blue). DMSO uused to dissolve ML228 was used as the vehicle. Scale bars, 30 µm. (n = 3) g, TER measurement of 2D-iRPE without or with ML228 treatment (n = 3). Data are presented as mean values +/− SEM. Two-way ANOVA, Tukey’s multiple comparisons test were used for statistical analysis. h, ZO-1 staining based morphometry analysis of individual cell area in vehicle and ML228-treated samples was performed, (n = 1644, number of cells). Data are presented as mean values with standard deviation. ANOVA and Tukey’s multiple comparisons test were used for statistical analysis.

Source data

Extended Data Fig. 7 Activation of HIF-1α in RPE induces type-I CNV-like phenotype in 3D-oBRB.

a-h, immunostaining of tissues with anti-CD31 (magenta), anti-HIF-1α (yellow) antibodies, and staining for F-ACTIN (cyan), and nuclei (blue). Tissues were treated with either vehicle (DMSO, a,e), or ML228 (2 μM) on apical side of RPE only (b,f), or basal side of choroid only (c,g), or both sides (d,h). Red arrowheads indicate type-I CNV-like phenotype, white arrowheads indicate examples of HIF-1α translocation to the nuclei. (n = 3), scale bars, 50 μm. i, TER measurements normalized to ctrl. (n = 6). Data are presented as mean values +/− SEM. ANOVA and Tukey’s multiple comparisons test. j, k, pseudo 3D-projected side views of 3D-oBRB immunostained with anti-CD31 (magenta), anti-COL IV (yellow), anti-LAMININ (cyan) antibodies, and nuclei (blue). Tissues were treated with either vehicle (DMSO, j), or ML228 (2 μM) on apical side of RPE only (k). Arrowheads indicate type-I CNV-like phenotype in ML228-treated (k) tissues with choriocapillaris (CC) penetrating through the Bruch’s membrane (BM). (n = 3), scale bars, 10 μm.

Source data

Extended Data Fig. 8 STAT3 overexpression in the RPE induces type-I CNV-like phenotype in 3D-oBRB.

a-l, en face views (a-h), and pseudo 3D-projected side views (i, j) of 3D-oBRB immunostained at week 6 with anti-CD31(magenta), anti-STAT3 (yellow) antibodies, and stained for nuclei (blue), containing wildtype iRPE (a-d, i), STAT3 overexpressing iRPE (e-h, j). BM – Bruch’s membrane, CC – choriocapillaris. N = 3. Scale bars, 50 μm (a-c, e-g), 10 μm (i, j). k, TER measurements normalized to control from 2D-iRPE monoculture. (N = 8). Data are presented as mean values +/− SEM. Unpaired t-test was used for statistical analysis.

Source data

Extended Data Fig. 9 Bevacizumab suppresses type-I CNV-like phenotype in 3D-oBRB.

a-c, Images of deep choroidal regions of (a) vehicle, (b) ML228, (c) ML228 + Bevacizumab treated 3D-oBRB, immunostained for CD31 (red) and stained for Hoechst (blue). Scale bars, 350 μm. (n = 4). d-h, en face views (d-g), and pseudo 3D-projected side views (h) of STAT3 overexpressing 3D-oBRB treated with Bevacizumab immunostained at week 6 with anti-CD31(magenta), anti-STAT3 (yellow) antibodies, and stained for nuclei (blue). BM – Bruch’s membrane, CC – choriocapillaris. N = 3. Scale bars, 50 μm (d-g), 10 μm (h). i, TER measurements normalized to control of STAT3 overexpressing 3D-oBRB and STAT3 overexpressing 3D-oBRB treated with Bevacizumab. (n = 4), Data are presented as mean values + /- SEM. One-way ANOVA and Tukey’s multiple comparisons test were used for statistical analysis.

Source data

Supplementary information

Supplementary information

Supplementary Tables 1–4, Supplementary Figs 1–21, legends for Supplementary Videos 1–7, Angiogenesis quantification MATLAB code, and Supplementary Protocol.

Reporting Summary

Supplementary Video 1

Bioprinting of vascularized tissue with GFP-positive ECs and VEGF-dependent angiogenesis from day 4 to day 6.

Supplementary Video 2

Pericytes and EC tubes in the context of 3D vascularized tissue at day 7.

Supplementary Video 3

3D-oBRB tissue model.

Supplementary Video 4

ELASTIN and LAMININ formation in 3D-oBRB tissue model (z-stack).

Supplementary Video 5

ELASTIN and LAMININ formation in 3D-oBRB tissue model.

Supplementary Video 6

Complement induced dry AMD model.

Supplementary Video/ Movie 7

HIF-1α induced CNV in 3D-oBRB with anti-VEGF (Bevacizumab) treatment.

Supplementary Data 1

Statistical source data for Supplementary Fig. 4.

Supplementary Data 2

Unprocessed gels or blots, unprocessed figure for Supplementary Fig. 21.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data

Source Data Fig. 6

Statistical source data and source data (Fig. 6.zip) is on Figshare (https://doi.org/10.6084/m9.figshare.21300198)

Source Data Extended Data Fig 6

Statistical source data.

Source Data Extended Data Fig 7

Statistical source data.

Source Data Extended Data Fig 8

Statistical source data.

Source Data Extended Data Fig 9

Statistical source data.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, M.J., Quinn, R., Nguyen, E. et al. Bioprinted 3D outer retina barrier uncovers RPE-dependent choroidal phenotype in advanced macular degeneration. Nat Methods 20, 149–161 (2023). https://doi.org/10.1038/s41592-022-01701-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-022-01701-1

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research