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.

  • Brief Communication
  • Published:

Reliability of human cortical organoid generation

Nature Methods volume 16, pages 75–78 (2019)Cite this article

Subjects

Abstract

The differentiation of pluripotent stem cells in three-dimensional cultures can recapitulate key aspects of brain development, but protocols are prone to variable results. Here we differentiated multiple human pluripotent stem cell lines for over 100 d using our previously developed approach to generate brain-region-specific organoids called cortical spheroids and, using several assays, found that spheroid generation was highly reliable and consistent. We anticipate the use of this approach for large-scale differentiation experiments and disease modeling.

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: Success of differentiation and transcriptional reliability of human cortical spheroids.
Fig. 2: Single-cell characterization of human cortical spheroids.

Similar content being viewed by others

Data availability

Gene expression data are available in the Gene Expression Omnibus (GEO) under accession numbers GSE93811, GSE107771 and GSE120700. The data that support the findings of this study are available on request from the corresponding author.

References

  1. Di Lullo, E. & Kriegstein, A. R. Nat. Rev. Neurosci. 18, 573–584 (2017).

    Article  Google Scholar 

  2. Pașca, S. P. Nature 553, 437–445 (2018).

    Google Scholar 

  3. Kelava, I. & Lancaster, M. A. Cell Stem Cell 18, 736–748 (2016).

    Article  CAS  Google Scholar 

  4. Bershteyn, M. et al. Cell Stem Cell 20, 435–449 (2017).

    Article  CAS  Google Scholar 

  5. Mariani, J. et al. Cell 162, 375–390 (2015).

    Article  CAS  Google Scholar 

  6. Lancaster, M. A. et al. Nature 501, 373–379 (2013).

    Article  CAS  Google Scholar 

  7. Sloan, S. A. et al. Neuron 95, 779–790 (2017).

    Article  CAS  Google Scholar 

  8. Qian, X. et al. Cell 165, 1238–1254 (2016).

    Article  CAS  Google Scholar 

  9. Blair, J. D., Hockemeyer, D. & Bateup, H. S. Nat. Med. 24, 1568–1578 (2018).

    Article  CAS  Google Scholar 

  10. Paşca, A. M. et al. Nat. Methods 12, 671–678 (2015).

    Article  Google Scholar 

  11. Sloan, S. A., Andersen, J., Pașca, A. M., Birey, F. & Pașca, S. P. Nat. Protoc. 13, 2062–2085 (2018).

    Article  CAS  Google Scholar 

  12. Birey, F. et al. Nature 545, 54–59 (2017).

    Article  CAS  Google Scholar 

  13. Stein, J. L. et al. Neuron 83, 69–86 (2014).

    Article  CAS  Google Scholar 

  14. BrainSpan. BrainSpan: Atlas of the Developing Human Brain http://www.brainspan.org (2013).

  15. Fan, H. C., Fu, G. K. & Fodor, S. P. Science 347, 1258367 (2015).

    Article  Google Scholar 

  16. Quadrato, G. et al. Nature 545, 48–53 (2017).

    Article  CAS  Google Scholar 

  17. Camp, J. G. et al. Proc. Natl Acad. Sci. USA 112, 15672–15677 (2015).

    Article  CAS  Google Scholar 

  18. Pașca, S. P. et al. Nat. Med. 17, 1657–1662 (2011).

    Article  Google Scholar 

  19. Gallego Romero, I. et al. eLife 4, e07103 (2015).

    Article  Google Scholar 

  20. Yoon, S. J. & Pașca, S. P. Protoc. Exch. https://doi.org/10.1038/protex.2018.123 (2018).

  21. Dobin, A. et al. Bioinformatics 29, 15–21 (2013).

    Article  CAS  Google Scholar 

  22. Li, B. & Dewey, C. N. BMC Bioinformatics 12, 323 (2011).

    Article  CAS  Google Scholar 

  23. Oldham, M. C., Langfelder, P. & Horvath, S. BMC Syst. Biol. 6, 63 (2012).

    Article  Google Scholar 

  24. Johnson, W. E., Li, C. & Rabinovic, A. Biostatistics 8, 118–127 (2007).

    Article  Google Scholar 

  25. McKenna, A. et al. Genome Res. 20, 1297–1303 (2010).

    Article  CAS  Google Scholar 

  26. Purcell, S. et al. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  Google Scholar 

  27. Liao, Y., Smyth, G. K. & Shi, W. Bioinformatics 30, 923–930 (2014).

    Article  CAS  Google Scholar 

  28. Robinson, M. D., McCarthy, D. J. & Smyth, G. K. Bioinformatics 26, 139–140 (2010).

    Article  CAS  Google Scholar 

  29. Ritchie, M. E. et al. Nucleic Acids Res. 43, e47 (2015).

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge support from J. Dreux and J. Lai (at BD Genomics) for running the pipeline and Data View troubleshooting. This work was supported by the US National Institutes of Health (NIH) BRAINS Award (MH107800), the MQ Fellow Award, the NYSCF Robertson Stem Cell Investigator Award, the Donald E. and Delia B. Baxter Foundation Award, the Stanford Neurosciences Institute’s Brain Rejuvenation Project, the Kwan Research Fund, a NARSAD Independent Investigator Award from the Brain & Behaviour Research Foundation (BBRF), and Stanford Start-up Funds (to S.P.P.); the California Institute of Regenerative Medicine (CIRM) and NIH U01 (MH115745) (to D.H.G. and S.P.P.); CIRM Bridges Program (to L.S.E.); a Stanford School of Medicine Dean’s Postdoctoral Fellowship (to Y.M.); a National Science Foundation (NSF) Graduate Research Fellowship (to R.M.M.); NIH K12-HD000850 (Pediatric Scientist Development Program) and a Stanford Child Health Research Institute Fellowship (to A.M.P); and the Autism Science Foundation Fellowship (to A.G.).

Author information

Authors and Affiliations

  1. Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA

    Se-Jin Yoon, Lubayna S. Elahi, Rebecca M. Marton, Omer Revah, Yuki Miura & Sergiu P. Pașca

  2. Department of Pediatrics, Division of Neonatology, Stanford University School of Medicine, Stanford, CA, USA

    Anca M. Pașca

  3. Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA

    Aaron Gordon & Daniel H. Geschwind

  4. BD Biosciences, Menlo Park, CA, USA

    Elisabeth M. Walczak, Gwendolyn M. Holdgate & H. Christina Fan

  5. Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA

    John R. Huguenard

  6. Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA

    Daniel H. Geschwind

  7. Human Brain Organogenesis Program, Stanford University, Stanford, CA, USA

    Sergiu P. Pașca

Authors
  1. Se-Jin Yoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lubayna S. Elahi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Anca M. Pașca
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rebecca M. Marton
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Aaron Gordon
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Omer Revah
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yuki Miura
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Elisabeth M. Walczak
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Gwendolyn M. Holdgate
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. H. Christina Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. John R. Huguenard
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Daniel H. Geschwind
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Sergiu P. Pașca
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.J.Y., R.M.M. and S.P.P. developed the differentiation method. S.J.Y. and L.S.E. performed differentiation experiments. S.J.Y., L.S.E., A.M.P., R.M.M. and Y.M. characterized the protocol. E.M.W., G.M.H. and H.C.F. performed the single-cell transcriptomics experiments and analysis. A.G. and D.H.G. performed the RNA-seq and analysis. O.R., S.P.P. and J.R.H. designed, conducted or analyzed the electrophysiological experiments. S.J.Y. and S.P.P. wrote the manuscript with input from all other authors. S.P.P. supervised the work.

Corresponding author

Correspondence to Sergiu P. Pașca.

Ethics declarations

Competing interests

Stanford University has filed a provisional patent application that covers the generation of region-specific neural spheroids (US Application Serial No. 15/158,408). H.C.F., E.M.W. and G.M.H. were employees of BD Genomics during this study.

Additional information

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

Integrated supplementary information

Supplementary Figure 1

(a) Example images of hiPSC maintained in feeder-free conditions, aggregates of dissociated hiPSCs in AggreWell microwells shown the day before starting neural differentiation, at 24 h after aggregation, after dislodging and at day 10 in vitro. (b–d) Gene expression (relative to GAPDH) at day 25 of differentiation for (b) the ectoderm marker SOX2, the mesoderm marker BRACH, the endoderm marker SOX17, and (c) the forebrain marker SIX3, and (d) midbrain (FOXA2), hypothalamus (RAX), striatal (GSX2) or spinal cord (HOXB4), markers; n = 12 hiPSC lines from 11 subjects in hCS-FF except for RAX, HOXB4 where n = 8 hiPSC lines, and BRACH and SOX17 where n = 6 hiPSC lines. Mean ± s.e.m. are shown.

Supplementary Figure 2

(a) Example cryosection of a hCS-FF at day 75 stained for PAX6 (dorsal forebrain progenitors, magenta) and TBR2 (intermediate progenitor cells, green) showing the presence of a VZ-like region organized around a lumen and an SVZ-like region beyond the VZ. (b) Example cryosection of hCS-FF at day 73 of differentiation showing expression of the progenitor marker SOX2 and the outer radial glia marker HOPX. (c) Example cryosection of hCS-FF at day 73 of differentiation showing expression of RELN and TBR1. (d) Example cryosection of hCS-FF at day 130 of differentiation showing expression of deep layer marker TLE4 and the upper layer marker BRN2. (e) Example cryosections of hCS-FF derived from an α-tubulin-mEGFP hiPSC line showing expression of cleaved Caspase 3 (c-Cas3) and overall morphology of hCS-FF at various stages of differentiation in vitro.

Supplementary Figure 3

Rank–rank hypergeometric overlap (RRHO) between hCS-FF (a) and hCS-MEF (b) of day 100 of differentiation compared to day 25 versus all pairwise comparison of stages from developing human cerebral cortex (BrainSpan). #2 indicates the 4–8 PCW stage, #6 indicates the 19–24 PCW stage, while #8 indicated postnatal stages. Genes were sorted by log fold-change. Axes of individual plots are the rankings of the genes (x-axis: hCS data, y-axis: BrainSpan data). Higher overlap led to smaller P values (higher –log10(P values)) which are represented by redder areas. Bottom left and top right of each plot are the overlap of down- and upregulated genes in both datasets, respectively. One-sided rank–rank hypergeometric test; for day 25, n = 22 hCS-FF samples and n = 3 hCS-MEF samples; for day 100, n = 22 hCS-FF samples and n = 4 hCS-MEF samples.

Supplementary Figure 4

(a) Distribution of expression of the neuronal marker STMN2, the progenitor marker VIM, and of a set of genes, which are associated with the M cell cycle phase (n = 24,237 cells). (b) Correlation (log10 transformed mean of molecules per cell per gene) between hCS-MEF and each of the hCS-FF cultures or the hSS-MEF.

Supplementary Figure 5

Trajectories of selected marker genes during hCS-FF differentiation: neural progenitors related genes (SOX2, PAX6, FOXG1), general neuronal and glial markers (SLC17A7 also known as VGLUT1, MAP2, NCAM1, AQP4), deep layer-specific cortical genes (TBR1, CTIP2 also known as BLC11B, ETV1, RORB SOX5,), and upper layer cortical genes (SATB2, CUX2, TLE1). Trend lines are averages of all data points. Color and shape denote the protocol used to grow cortical spheroids: FF (red circles) or MEF (black triangles).

Supplementary Figure 6

(a) Whole cell current clamp slice recording from an AAV (DJ)-Syn1::mCherry+ neuron showing repetitive action potential firing in response to a depolarizing current injection (day 85–130; n = 13 neurons). (b) Single action potential waveform aligned to its first derivative. (c) Membrane responses after a 30 pA depolarizing current injection before and during application of the sodium channel blocker TTX (n = 3 neurons). (d) Voltage clamp recording at –70 mV showing spontaneous EPSCs, which are blocked by the glutamate receptor antagonists NBQX (20 μM) and APV (100 μM) (n = 13 neurons). (e) Quantification of the spontaneous EPSC rate before and during application of NBQX (20 μM) and APV (100 μM) in slices of hCS-FF at days 120–130 of differentiation (n = 13 cells; two-sided paired t-test ***P = 0.0004). (f) Example of a digitally reconstructed hCS-FF neuron infected with an AAV (DJ)-Syn1::ChR2-mCherry (in dissociated cultures). (g) Current clamp recording from the neuron shown in (f) showing action potential generation in response to a 2 ms blue light pulse delivered via fiber optic. (h) Membrane potential response to 5 ms-long blue light pulses delivered at increasing rates (8–32 Hz) showing frequency-dependent AP failures (n = 7 neurons). (i) Quantification of action potential success rate in AAV (DJ)-Syn1::ChR2-mCherry+ cells following blue light pulses delivered at increasing rates (8–32 Hz); shading indicates s.e.m.

Supplementary information

Supplementary Text and Figures

Supplementary Figs. 1–6 and Supplementary Tables 1, 2, and 4

Reporting Summary

Supplementary Table 3

Samples used for RNA-seq

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yoon, SJ., Elahi, L.S., Pașca, A.M. et al. Reliability of human cortical organoid generation. Nat Methods 16, 75–78 (2019). https://doi.org/10.1038/s41592-018-0255-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-018-0255-0

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing