Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture (original) (raw)

Accession codes

Primary accessions

Gene Expression Omnibus

References

  1. Dolmetsch, R. & Geschwind, D.H. The human brain in a dish: the promise of iPSC-derived neurons. Cell 145, 831–834 (2011).
    Article CAS Google Scholar
  2. Takahashi, K. & Yamanaka, S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 126, 663–676 (2006).
    Article CAS Google Scholar
  3. Tabar, V. & Studer, L. Pluripotent stem cells in regenerative medicine: challenges and recent progress. Nat. Rev. Genet. 15, 82–92 (2014).
    Article CAS Google Scholar
  4. Brennand, K.J., Simone, A., Tran, N. & Gage, F.H. Modeling psychiatric disorders at the cellular and network levels. Mol. Psychiatry 17, 1239–1253 (2012).
    Article CAS Google Scholar
  5. Pas¸ca, S.P., Panagiotakos, G. & Dolmetsch, R.E. Generating human neurons in vitro and using them to understand neuropsychiatric disease. Annu. Rev. Neurosci. 37, 479–501 (2014).
    Article Google Scholar
  6. Mariani, J. et al. Modeling human cortical development in vitro using induced pluripotent stem cells. Proc. Natl. Acad. Sci. USA 109, 12770–12775 (2012).
    Article CAS Google Scholar
  7. Kadoshima, T. et al. Self-organization of axial polarity, inside-out layer pattern, and species-specific progenitor dynamics in human ES cell-derived neocortex. Proc. Natl. Acad. Sci. USA 110, 20284–20289 (2013).
    Article CAS Google Scholar
  8. Lancaster, M.A. et al. Cerebral organoids model human brain development and microcephaly. Nature 501, 373–379 (2013).
    Article CAS Google Scholar
  9. Brennand, K.J. & Gage, F.H. Modeling psychiatric disorders through reprogramming. Dis. Model. Mech. 5, 26–32 (2012).
    Article Google Scholar
  10. Chambers, S.M. et al. Highly efficient neural conversion of human ES and iPS cells by dual inhibition of SMAD signaling. Nat. Biotechnol. 27, 275–280 (2009).
    Article CAS Google Scholar
  11. Sarnat, H.B., Nochlin, D. & Born, D.E. Neuronal nuclear antigen (NeuN): a marker of neuronal maturation in early human fetal nervous system. Brain Dev. 20, 88–94 (1998).
    Article CAS Google Scholar
  12. Stein, J.L. et al. A quantitative framework to evaluate modeling of cortical development by neural stem cells. Neuron 83, 69–86 (2014).
    Article CAS Google Scholar
  13. Kang, H.J. et al. Spatio-temporal transcriptome of the human brain. Nature 478, 483–489 (2011).
    Article CAS Google Scholar
  14. Miller, J.A. et al. Transcriptional landscape of the prenatal human brain. Nature 508, 199–206 (2014).
    Article CAS Google Scholar
  15. Englund, C. et al. Pax6, Tbr2, and Tbr1 are expressed sequentially by radial glia, intermediate progenitor cells, and postmitotic neurons in developing neocortex. J. Neurosci. 25, 247–251 (2005).
    Article CAS Google Scholar
  16. Hansen, D.V., Lui, J.H., Parker, P.R. & Kriegstein, A.R. Neurogenic radial glia in the outer subventricular zone of human neocortex. Nature 464, 554–561 (2010).
    Article CAS Google Scholar
  17. Weissman, T., Noctor, S.C., Clinton, B.K., Honig, L.S. & Kriegstein, A.R. Neurogenic radial glial cells in reptile, rodent and human: from mitosis to migration. Cereb. Cortex 13, 550–559 (2003).
    Article Google Scholar
  18. Taverna, E. & Huttner, W.B. Neural progenitor nuclei IN motion. Neuron 67, 906–914 (2010).
    Article CAS Google Scholar
  19. Meyer, G. & Goffinet, A.M. Prenatal development of reelin-immunoreactive neurons in the human neocortex. J. Comp. Neurol. 397, 29–40 (1998).
    Article CAS Google Scholar
  20. Saito, T. et al. Neocortical layer formation of human developing brains and lissencephalies: consideration of layer-specific marker expression. Cereb. Cortex 21, 588–596 (2011).
    Article Google Scholar
  21. Alcamo, E.A. et al. Satb2 regulates callosal projection neuron identity in the developing cerebral cortex. Neuron 57, 364–377 (2008).
    Article CAS Google Scholar
  22. Britanova, O. et al. Satb2 is a postmitotic determinant for upper-layer neuron specification in the neocortex. Neuron 57, 378–392 (2008).
    Article CAS Google Scholar
  23. Sugitani, Y. et al. Brn-1 and Brn-2 share crucial roles in the production and positioning of mouse neocortical neurons. Genes Dev. 16, 1760–1765 (2002).
    Article CAS Google Scholar
  24. Zeng, H. et al. Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures. Cell 149, 483–496 (2012).
    Article CAS Google Scholar
  25. Shen, Q. et al. The timing of cortical neurogenesis is encoded within lineages of individual progenitor cells. Nat. Neurosci. 9, 743–751 (2006).
    Article CAS Google Scholar
  26. Bayer, S.A. & Altman, J. Neocortical Development (Raven Press, New York, 1991).
  27. Micheva, K.D. & Smith, S.J. Array tomography: a new tool for imaging the molecular architecture and ultrastructure of neural circuits. Neuron 55, 25–36 (2007).
    Article CAS Google Scholar
  28. Foo, L.C. et al. Development of a method for the purification and culture of rodent astrocytes. Neuron 71, 799–811 (2011).
    Article CAS Google Scholar
  29. McCarthy, K.D. & de Vellis, J. Preparation of separate astroglial and oligodendroglial cell cultures from rat cerebral tissue. J. Cell Biol. 85, 890–902 (1980).
    Article CAS Google Scholar
  30. Zamanian, J.L. et al. Genomic analysis of reactive astrogliosis. J. Neurosci. 32, 6391–6410 (2012).
    Article CAS Google Scholar
  31. Brown, A.M. & Ransom, B.R. Astrocyte glycogen and brain energy metabolism. Glia 55, 1263–1271 (2007).
    Article Google Scholar
  32. Pas¸ca, S.P. et al. Using iPSC-derived neurons to uncover cellular phenotypes associated with Timothy syndrome. Nat. Med. 17, 1657–1662 (2011).
    Article Google Scholar
  33. Brennand, K.J. et al. Modelling schizophrenia using human induced pluripotent stem cells. Nature 473, 221–225 (2011).
    Article CAS Google Scholar
  34. Marchetto, M.C. et al. A model for neural development and treatment of Rett syndrome using human induced pluripotent stem cells. Cell 143, 527–539 (2010).
    Article CAS Google Scholar
  35. Pfrieger, F.W. & Barres, B.A. Synaptic efficacy enhanced by glial cells in vitro. Science 277, 1684–1687 (1997).
    Article CAS Google Scholar
  36. Ullian, E.M., Sapperstein, S.K., Christopherson, K.S. & Barres, B.A. Control of synapse number by glia. Science 291, 657–661 (2001).
    Article CAS Google Scholar
  37. Krencik, R., Weick, J.P., Liu, Y., Zhang, Z.J. & Zhang, S.C. Specification of transplantable astroglial subtypes from human pluripotent stem cells. Nat. Biotechnol. 29, 528–534 (2011).
    Article CAS Google Scholar
  38. Meyer, K. et al. Direct conversion of patient fibroblasts demonstrates non-cell autonomous toxicity of astrocytes to motor neurons in familial and sporadic ALS. Proc. Natl. Acad. Sci. USA 111, 829–832 (2014).
    Article CAS Google Scholar
  39. Allen, N.J. et al. Astrocyte glypicans 4 and 6 promote formation of excitatory synapses via GluA1 AMPA receptors. Nature 486, 410–414 (2012).
    Article CAS Google Scholar
  40. Eroglu, C. et al. Gabapentin receptor alpha2delta-1 is a neuronal thrombospondin receptor responsible for excitatory CNS synaptogenesis. Cell 139, 380–392 (2009).
    Article CAS Google Scholar
  41. Yazawa, M. et al. Using induced pluripotent stem cells to investigate cardiac phenotypes in Timothy syndrome. Nature 471, 230–234 (2011).
    Article CAS Google Scholar
  42. Cahoy, J.D. et al. A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for understanding brain development and function. J. Neurosci. 28, 264–278 (2008).
    Article CAS Google Scholar
  43. Dugas, J.C., Tai, Y.C., Speed, T.P., Ngai, J. & Barres, B.A. Functional genomic analysis of oligodendrocyte differentiation. J. Neurosci. 26, 10967–10983 (2006).
    Article CAS Google Scholar
  44. Micheva, K.D., Busse, B., Weiler, N.C., O'Rourke, N. & Smith, S.J. Single-synapse analysis of a diverse synapse population: proteomic imaging methods and markers. Neuron 68, 639–653 (2010).
    Article CAS Google Scholar

Download references

Acknowledgements

We thank R. Dolmetsch, R. O'Hara, U. Francke and J. Hallmayer for valuable scientific advice and discussions, and also acknowledge E. Engleman and the Stanford Blood Flow Cytometry Center for technical advice and support, J. Ou for assistance with RNA preparation, and D. Castaneda-Castellanos for assistance with live imaging. This work was supported by a NARSAD Young Investigator Award (Behavioral and Brain Foundation), US National Institute of Mental Health (NIMH) 1R01MH100900 and 1R01MH100900-02S1, MQ Fellow Award and Startup Funds from Stanford University (to S.P.P.); NIMH R01 MH099555-03 (to B.A.B.); NIMH T32GM007365, F30MH106261 and Bio-X Predoctoral Fellowship (to or supporting S.A.S.); NIMH 5R37 MH060233 and 5R01 MH094714 (to D.H.G.); NIH R01NS075252, R21MH099797 and R01NS092474 (to S.J.S.); and the DGIST R&D Program of the Korean Ministry of Science and ICT & Future Planning, 14-BD-16 (to C.H.K.).

Author information

Author notes

  1. Anca M Paşca and Steven A Sloan: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Pediatrics, Division of Neonatology, Stanford University School of Medicine, Stanford, California, USA
    Anca M Paşca
  2. Department of Neurobiology, Stanford University School of Medicine, Stanford, California, USA
    Steven A Sloan, Laura E Clarke & Ben A Barres
  3. Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, California, USA
    Yuan Tian & Daniel H Geschwind
  4. Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California, USA
    Yuan Tian & Daniel H Geschwind
  5. Interdepartmental Ph.D. Program in Bioinformatics, University of California, Los Angeles, California, USA
    Yuan Tian & Daniel H Geschwind
  6. Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
    Christopher D Makinson & John R Huguenard
  7. Department of Psychiatry & Behavioral Sciences, Center for Sleep Sciences and Medicine, Stanford University School of Medicine, Stanford, California, USA
    Nina Huber, Jin-Young Park & Sergiu P Paşca
  8. Department of Pharmacology, Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Korea
    Chul Hoon Kim
  9. BK21 PLUS Project for Medical Science, Yonsei University College of Medicine, Seoul, Korea
    Chul Hoon Kim
  10. Department of Molecular and Cellular Physiology, Beckman Center, Stanford University School of Medicine, Stanford, California, USA
    Nancy A O'Rourke & Stephen J Smith
  11. Department of Pathology, Blood Center, Stanford University School of Medicine, Stanford, California, USA
    Khoa D Nguyen
  12. Department of Synapse Biology, Allen Institute for Brain Science, Seattle, Washington, USA
    Stephen J Smith

Authors

  1. Anca M Paşca
  2. Steven A Sloan
  3. Laura E Clarke
  4. Yuan Tian
  5. Christopher D Makinson
  6. Nina Huber
  7. Chul Hoon Kim
  8. Jin-Young Park
  9. Nancy A O'Rourke
  10. Khoa D Nguyen
  11. Stephen J Smith
  12. John R Huguenard
  13. Daniel H Geschwind
  14. Ben A Barres
  15. Sergiu P Paşca

Contributions

A.M.P., S.A.S. and S.P.P. conceived the project. A.M.P., S.A.S., L.E.C., Y.T., C.D.M., C.H.K., J.-Y.P., N.A.O'R., K.D.N., N.H., S.J.S., J.R.H., D.H.G., B.A.B. and S.P.P. planned and/or executed experiments. A.M.P., S.A.S. and S.P.P. wrote the paper with input from all authors. S.P.P. supervised all aspects of the work.

Corresponding author

Correspondence toSergiu P Paşca.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Antibody specificity.

Panel showing the specificity of the antibodies against NEUN, GFAP, FOXG1, PAX6 (Rb), PAX6 (Mo) in negative cells (HEK293T). The last row shows background immunostaining for secondary-only conditions. All images were collected at a 500 ms exposure.

Supplementary Figure 2 Transcriptional analyses and mapping of neuronal cultures derived from hiPSCs using a monolayer approach.

The machine learning algorithm CoNTExT, which matches transcriptomes to human brain development, was used to predict the in vivo temporal identity of neural progenitors and neurons differentiated from hiPSC using a monolayer approach (adapted from Fig. 7 in Stein et. al., 2014). In contrast to the hCSs in Fig. 1e that reach up to fetal stage 6, these cultures map to earlier stages of brain development.

Stein, J.L., Torre-Ubieta, L., Tian, Y., Parikshak, N.P., Hernandez, I.A., Marchetto, M.C., Baker, D.K., Lu, D., Hinman, C.R., Lowe, J.K., Wexler, E.M., Muotri, A.R., Gage, F.H., Kosik, K.S., and Geschwind, D.H. A Quantitative Framework to Evaluate Modeling of Cortical Development by Neural Stem Cells Neuron 83, 69-86 (2014).

Supplementary Figure 4 Variability in the generation of hCSs.

(a) Proportion of neurons (mean ± s.e.m.) expressing CTIP2 and SATB2 at day 40 of differentiation. Multiple spheroids differentiated at the same time from one hiPSC line. Standard deviation is 2.9% for CTIP2 and 1.5% for SATB2. (b) Proportion of neurons (mean ± s.e.m.) expressing CTIP2 and SATB2 at day 76 of differentiation. The same hiPSC line was differentiated in two different experiments at two different times (multiple hCS per differentiation). Two-way ANOVA, F1,14 = 0.1940, P = 0.66 for hiPSC lines; multiple comparison test P > 0.05. (c) Proportion of neurons (mean ± s.e.m.) expressing CTIP2 and SATB2 at day 76 of differentiation. Two hiPSC lines derived from two individuals were differentiated at two different times (multiple hCS per differentiation). Two-way ANOVA, F1,14 = 1.257, P = 0.28; multiple comparison test P > 0.05.

Supplementary Figure 5 Flow cytometry analysis of hCSs.

(a) Example of scatter plots for each of the antibodies used (first three rows) and the secondary only control conditions (fourth row). The marker of interest is presented on the x-axis and the threshold gate is based on the negative control samples (cells stained with secondary antibodies alone). The y-axis represents a "dump channel", a BV-421 fluorescent channel in which the cells were not stained with any fluorophores. Any positive signals on this BV-421 channel represent highly auto-flourescent cells or false positives and were excluded from the actual positive gates. (b) Quantification of the proportion of cells expressing various markers at day 76 of in vitro differentiation as assessed by flow cytometry.

Supplementary Figure 6 Expression of activation markers in hCSs before and after exposure to serum.

hCSs plated in monolayer were cultured in Neurobasal–B27 media with our without 20% serum (FBS). After 5 days, cells were harvested and the expression of genes associated with astrocyte activation (GFAP, VIM, LCN2) was measured by qPCR (t-tests with multiple comparison corrections using the Holm-Sidak method; n = 3 for each gene, *, P < 0.05; **, P < 0.01; ***, P < 0.001).

Supplementary Figure 7 Electrophysiology (hCSs plated in monolayer).

(a) Pharmacology of synaptic currents in neurons derived in hCS and plated in monolayer (at –70 mV). The frequency of EPSCs was abolished by NBQX (25 μM) and D-AP5 (50 μM) (paired t-test, n = 11 cells, P = 0.001), and was significantly reduced by 1 μM TTX (Wilcoxon signed-rank test, n = 10, P = 0.002). (b) TTX significantly reduced the amplitude of the EPSCs (P < 0.0001, paired t-test, versus ACSF, n = 10 cells).

Supplementary Figure 8 Electrophysiology (hCS slice recordings).

(a) Representative trace of a whole-cell current-clamp recording in an acute hCS slice preparation. Current injections (6 or 12 pA steps from –65 mV) produce sustained action potential generation. (b) Representative averaged trace of 53 sEPSCs in an individual hCS neuron under control conditions. (c) EPSCs were blocked by bath application of kynurenic acid in sliced hCSs (t-test, n = 6 cells; P = 0.0008). (d) Examples of voltage clamp recordings in two different hCSs showing EPSCs after electrical stimulation in an acute hCS slice preparation. The electrical stimulation artifact is designated by a red dot. (e) EPSC frequency 1s prior compared to 2s after electrical stimulation (t-test, n = 3 cells; P = 0.02) (f) Left: Representative traces of spontaneous action potentials (top three traces) and compound EPSPs (bottom three traces). Right: Representative examples of stimulus-evoked action potentials (top three traces) and compound EPSPs (bottom three traces). The electrical stimulation artifact is designated by a red dot.

Supplementary information

Rights and permissions

About this article

Cite this article

Paşca, A., Sloan, S., Clarke, L. et al. Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture.Nat Methods 12, 671–678 (2015). https://doi.org/10.1038/nmeth.3415

Download citation