Predicting the functional states of human iPSC-derived neurons with single-cell RNA-seq and electrophysiology

Abstract

Human neural progenitors derived from pluripotent stem cells develop into electrophysiologically active neurons at heterogeneous rates, which can confound disease-relevant discoveries in neurology and psychiatry. By combining patch clamping, morphological and transcriptome analysis on single-human neurons in vitro, we defined a continuum of poor to highly functional electrophysiological states of differentiated neurons. The strong correlations between action potentials, synaptic activity, dendritic complexity and gene expression highlight the importance of methods for isolating functionally comparable neurons for in vitro investigations of brain disorders. Although whole-cell electrophysiology is the gold standard for functional evaluation, it often lacks the scalability required for disease modeling studies. Here, we demonstrate a multimodal machine-learning strategy to identify new molecular features that predict the physiological states of single neurons, independently of the time spent in vitro. As further proof of concept, we selected one of the potential neurophysiological biomarkers identified in this study—GDAP1L1—to isolate highly functional live human neurons in vitro.

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References

  1. 1

    Greig LC, Woodworth MB, Galazo MJ, Padmanabhan H, Macklis JD . Molecular logic of neocortical projection neuron specification, development and diversity. Nat Rev Neurosci 2013; 14: 755–769.

    CAS  Article  Google Scholar 

  2. 2

    Molyneaux BJ, Arlotta P, Menezes JRL, Macklis JD . Neuronal subtype specification in the cerebral cortex. Nat Rev Neurosci 2007; 8: 427–437.

    CAS  Article  Google Scholar 

  3. 3

    Cho M-S, Hwang D-Y, Kim D-W . Efficient derivation of functional dopaminergic neurons from human embryonic stem cells on a large scale. Nat Protoc 2008; 3: 1888–1894.

    CAS  Article  Google Scholar 

  4. 4

    Vadodaria KC, Mertens J, Paquola A, Bardy C, Li X, Jappelli R et al. Generation of functional human serotonergic neurons from fibroblasts. Mol Psychiatry 2015; 21: 49–61.

    Article  Google Scholar 

  5. 5

    Shi Y, Kirwan P, Smith J, Robinson HPC, Livesey FJ . Human cerebral cortex development from pluripotent stem cells to functional excitatory synapses. Nat Neurosci 2012; 15: 477–486.

    CAS  Article  Google Scholar 

  6. 6

    Boyer LF, Campbell B, Larkin S, Mu Y, Gage FH . Dopaminergic differentiation of human pluripotent cells. Curr Protoc Stem Cell Biol 2012; Chapter 1: Unit1H.6.

    PubMed  Google Scholar 

  7. 7

    Mertens J, Marchetto MC, Bardy C, Gage FH . Evaluating cell reprogramming, differentiation and conversion technologies in neuroscience. Nat Rev Neurosci 2016; 17: 424–437.

    CAS  Article  Google Scholar 

  8. 8

    Kirwan P, Turner-Bridger B, Peter M, Momoh A, Arambepola D, Robinson HPC et al. Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro. Development 2015; 142: 3178–3187.

    CAS  Article  Google Scholar 

  9. 9

    Wernig M, Zhao J-P, Pruszak J, Hedlund E, Fu D, Soldner F et al. Neurons derived from reprogrammed fibroblasts functionally integrate into the fetal brain and improve symptoms of rats with Parkinson's disease. Proc Natl Acad Sci USA 2008; 105: 5856–5861.

    CAS  Article  Google Scholar 

  10. 10

    Pang ZP, Yang N, Vierbuchen T, Ostermeier A, Fuentes DR, Yang TQ et al. Induction of human neuronal cells by defined transcription factors. Nature 2011; 476: 220–223.

    CAS  Article  Google Scholar 

  11. 11

    Chanda S, Ang CE, Davila J, Pak C, Mall M, Lee QY et al. Generation of induced neuronal cells by the single reprogramming factor ASCL1. Stem Cell Reports 2014; 3: 282–296.

    CAS  Article  Google Scholar 

  12. 12

    Zhang Y, Pak C, Han Y, Ahlenius H, Zhang Z, Chanda S et al. Rapid single-step induction of functional neurons from human pluripotent stem cells. Neuron 2013; 78: 785–798.

    CAS  Article  Google Scholar 

  13. 13

    Bardy C, Van den Hurk M, Eames T, Marchand C, Hernandez RV, Kellogg M et al. Neuronal medium that supports basic synaptic functions and activity of human neurons in vitro. Proc Natl Acad Sciences 2015; 112: E2725–E2734.

    CAS  Article  Google Scholar 

  14. 14

    Prilutsky D, Palmer NP, Smedemark-Margulies N, Schlaeger TM, Margulies DM, Kohane IS . iPSC-derived neurons as a higher-throughput readout for autism: promises and pitfalls. Trends Mol Med 2014; 20: 91–104.

    CAS  Article  Google Scholar 

  15. 15

    Belinsky GS, Moore AR, Short SM, Rich MT, Antic SD . Physiological properties of neurons derived from human embryonic stem cells using a dibutyryl cyclic AMP-based protocol. Stem Cells Dev 2011; 20: 1733–1746.

    CAS  Article  Google Scholar 

  16. 16

    Wu H, Xu J, Pang ZP, Ge W, Kim KJ, Blanchi B et al. Integrative genomic and functional analyses reveal neuronal subtype differentiation bias in human embryonic stem cell lines. Proc Natl Acad Sci USA 2007; 104: 13821–13826.

    CAS  Article  Google Scholar 

  17. 17

    Hu BY, Weick JP, Yu J, Ma LX, Zhang XQ, Thomson JA et al. Neural differentiation of human induced pluripotent stem cells follows developmental principles but with variable potency. Proc Natl Acad Sci 2010; 107: 4335–4340.

    CAS  Article  Google Scholar 

  18. 18

    Tang X, Zhou L, Wagner AM, Marchetto MC, Muotri AR, Gage FH et al. Astroglial cells regulate the developmental timeline of human neurons differentiated from induced pluripotent stem cells. Stem Cell Res 2013; 11: 743–757.

    CAS  Article  Google Scholar 

  19. 19

    Weick JP, Johnson MA, Skroch SP, Williams JC, Deisseroth K, Zhang S-C . Functional control of transplantable human ESC-derived neurons via optogenetic targeting. Stem Cells 2010; 28: 2008–2016.

    CAS  Article  Google Scholar 

  20. 20

    Yang N, Ng YH, Pang ZP, Südhof TC, Wernig M . Induced neuronal cells: how to make and define a neuron. Cell Stem Cell 2011; 9: 517–525.

    CAS  Article  Google Scholar 

  21. 21

    Geurts P, Ernst D, Wehenkel L . Extremely randomized trees. Mach Learn 2006; 63: 3–42.

    Article  Google Scholar 

  22. 22

    Marr RA, Guan H, Rockenstein E, Kindy M, Gage FH, Verma I et al. Neprilysin regulates amyloid Beta peptide levels. J Mol Neurosci 2004; 22: 5–11.

    Article  Google Scholar 

  23. 23

    Brennand KJ, Simone A, Jou J, Gelboin-Burkhart C, Tran N, Sangar S et al. Modelling schizophrenia using human induced pluripotent stem cells. Nature 2011; 473: 221–225.

    CAS  Article  Google Scholar 

  24. 24

    Dolmetsch R, Geschwind DH . The human brain in a dish: the promise of iPSC-derived neurons. Cell 2011; 145: 831–834.

    CAS  Article  Google Scholar 

  25. 25

    Shcheglovitov A, Shcheglovitova O, Yazawa M, Portmann T, Shu R, Sebastiano V et al. SHANK3 and IGF1 restore synaptic deficits in neurons from 22q13 deletion syndrome patients. Nature 2013; 503: 267–271.

    CAS  Article  Google Scholar 

  26. 26

    Wen Z, Nguyen HN, Guo Z, Lalli MA, Wang X, Su Y et al. Synaptic dysregulation in a human iPS cell model of mental disorders. Nature 2014; 515: 414–418.

    CAS  Article  Google Scholar 

  27. 27

    Lledo P-MM, Alonso M, Grubb MS . Adult neurogenesis and functional plasticity in neuronal circuits. Nat Rev Neurosci 2006; 7: 179–193.

    CAS  Article  Google Scholar 

  28. 28

    Trapnell C, Cacchiarelli D, Grimsby J, Pokharel P, Li S, Morse M et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol 2014; 32: 381–386.

    CAS  Article  Google Scholar 

  29. 29

    Tsetsenis T, Younts TJ, Chiu CQ, Kaeser PS, Castillo PE, Südhof TC . Rab3B protein is required for long-term depression of hippocampal inhibitory synapses and for normal reversal learning. Proc Natl Acad Sci 2011; 108: 14300–14305.

    CAS  Article  Google Scholar 

  30. 30

    Lewis S . Synaptic plasticity: a key player in presynaptic plasticity. Nat Rev Neurosci 2011; 12: 548–548.

    CAS  Article  Google Scholar 

  31. 31

    Pedrola L, Espert A, Wu X, Claramunt R, Shy ME, Palau F . GDAP1, the protein causing Charcot-Marie-Tooth disease type 4A, is expressed in neurons and is associated with mitochondria. Hum Mol Genet 2005; 14: 1087–1094.

    CAS  Article  Google Scholar 

  32. 32

    Lewis DA . The human brain revisited: opportunities and challenges in postmortem studies of psychiatric disorders. Neuropsychopharmacology 2002; 26: 143–154.

    Article  Google Scholar 

  33. 33

    Moore AR, Filipovic R, Mo Z, Rasband MN, Zecevic N, Antic SD . Electrical excitability of early neurons in the human cerebral cortex during the second trimester of gestation. Cereb Cortex 2009; 19: 1795–1805.

    Article  Google Scholar 

  34. 34

    Moore AR, Zhou W-L, Jakovcevski I, Zecevic N, Antic SD . Spontaneous electrical activity in the human fetal cortex in vitro. J Neurosci 2011; 31: 2391–2398.

    CAS  Article  Google Scholar 

  35. 35

    Nicholas CR, Chen J, Tang Y, Southwell DG, Chalmers N, Vogt D et al. Functional maturation of hPSC-derived forebrain interneurons requires an extended timeline and mimics human neural development. Cell Stem Cell 2013; 12: 573–586.

    CAS  Article  Google Scholar 

  36. 36

    Vierbuchen T, Ostermeier A, Pang ZP, Kokubu Y, Südhof TC, Wernig M . Direct conversion of fibroblasts to functional neurons by defined factors. Nature 2010; 463: 1035–1041.

    CAS  Article  Google Scholar 

  37. 37

    Eberwine J, Sul J-Y, Bartfai T, Kim J . The promise of single-cell sequencing. Nat Methods 2014; 11: 25–27.

    CAS  Article  Google Scholar 

  38. 38

    Saliba A-E, Westermann AJ, Gorski SA, Vogel J . Single-cell RNA-seq: advances and future challenges. Nucleic Acids Res 2014; 42: 8845–8860.

    CAS  Article  Google Scholar 

  39. 39

    Sandberg R . Entering the era of single-cell transcriptomics in biology and medicine. Nat Methods 2014; 11: 22–24.

    CAS  Article  Google Scholar 

  40. 40

    Shapiro E, Biezuner T, Linnarsson S . Single-cell sequencing-based technologies will revolutionize whole-organism science. Nat Rev Genet 2013; 14: 618–630.

    CAS  Article  Google Scholar 

  41. 41

    Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 2009; 6: 377–382.

    CAS  Article  Google Scholar 

  42. 42

    Picelli S, Björklund ÅK, Faridani OR, Sagasser S, Winberg G, Sandberg R . Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 2013; 10: 1096–1098.

    CAS  Article  Google Scholar 

  43. 43

    Wu AR, Neff NF, Kalisky T, Dalerba P, Treutlein B, Rothenberg ME et al. Quantitative assessment of single-cell RNA-sequencing methods. Nat Methods 2014; 11: 41–46.

    CAS  Article  Google Scholar 

  44. 44

    Islam S, Kjällquist U, Moliner A, Zajac P, Fan J-B, Lonnerberg P et al. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. Genome Res 2011; 21: 1160–1167.

    CAS  Article  Google Scholar 

  45. 45

    Islam S, Kjällquist U, Moliner A, Zajac P, Fan J-B, Lonnerberg P et al. Highly multiplexed and strand-specific single-cell RNA 5[prime] end sequencing. Nat Protoc 2012; 7: 813–828.

    CAS  Article  Google Scholar 

  46. 46

    Tang F, Barbacioru C, Nordman E, Li B, Xu N, Bashkirov VI et al. RNA-Seq analysis to capture the transcriptome landscape of a single cell. Nat Protoc 2010; 5: 516–535.

    CAS  Article  Google Scholar 

  47. 47

    Picelli S, Faridani OR, Björklund ÅK, Winberg G, Sagasser S, Sandberg R . Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc 2014; 9: 171–181.

    CAS  Article  Google Scholar 

  48. 48

    Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 2014; 344: 1396–1401.

    CAS  Article  Google Scholar 

  49. 49

    Toriello NM, Douglas ES, Thaitrong N, Hsiao SC, Francis MB, Bertozzi CR et al. Integrated microfluidic bioprocessor for single-cell gene expression analysis. Proc Natl Acad Sci 2008; 105: 20173–20178.

    CAS  Article  Google Scholar 

  50. 50

    Belinsky GS, Rich MT, Sirois CL, Short SM, Pedrosa E, Lachman HM et al. Patch-clamp recordings and calcium imaging followed by single-cell PCR reveal the developmental profile of 13 genes in iPSC-derived human neurons. Stem Cell Res 2014; 12: 101–118.

    CAS  Article  Google Scholar 

  51. 51

    Faragó N, Kocsis AK, Lovas S, Molnár G, Boldog E, Rózsa M et al. Digital PCR to determine the number of transcripts from single neurons after patch-clamp recording. BioTechniques 2013; 54: 327–336.

    Article  Google Scholar 

  52. 52

    Toledo-Rodriguez M, Markram H . Single-cell RT-PCR, a technique to decipher the electrical, anatomical, and genetic determinants of neuronal diversity. Methods Mol Biol 2007; 403: 123–139.

    CAS  Article  Google Scholar 

  53. 53

    Toledo-Rodriguez M, Blumenfeld B, Wu C, Luo J, Attali B, Goodman P et al. Correlation maps allow neuronal electrical properties to be predicted from single-cell gene expression profiles in rat neocortex. Cereb Cortex 2004; 14: 1310–1327.

    Article  Google Scholar 

  54. 54

    Subkhankulova, Yano K, Hugh PC Robinson, Livesey FJ . Grouping and classifying electrophysiologically-defined classes of neocortical neurons by single cell, whole-genome expression profiling. Front Mol Neurosci 2010; 3: 10.

    PubMed  PubMed Central  Google Scholar 

  55. 55

    Fuzik J, Zeisel A, Mate Z, Calvigioni D, Yanagawa Y, Szabo G et al. Integration of electrophysiological recordings with single-cell RNA-seq data identifies neuronal subtypes. Nat Biotechnol 2015; 34: 175–183.

    Article  Google Scholar 

  56. 56

    Cadwell CR, Palasantza A, Jiang X, Berens P, Deng Q, Yilmaz M et al. Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq. Nat Biotechnol 2015; 34: 199–203.

    Article  Google Scholar 

  57. 57

    Steward O, Wallace CS, Lyford GL, Worley PF . Synaptic activation causes the mRNA for the IEG arc to localize selectively near activated postsynaptic sites on dendrites. Neuron 1998; 21: 741–751.

    CAS  Article  Google Scholar 

  58. 58

    Cajigas IJ, Tushev G, Will TJ, tom Dieck S, Fuerst N, Schuman EM . The local transcriptome in the synaptic neuropil revealed by deep sequencing and high-resolution imaging. Neuron 2012; 74: 453–466.

    CAS  Article  Google Scholar 

  59. 59

    Bassell GJ, Warren ST . Fragile X syndrome: loss of local mRNA regulation alters synaptic development and function. Neuron 2008; 60: 201–214.

    CAS  Article  Google Scholar 

  60. 60

    Bagni C, Greenough WT . From mRNP trafficking to spine dysmorphogenesis: the roots of fragile X syndrome. Nat Rev Neurosci 2005; 6: 376–387.

    CAS  Article  Google Scholar 

  61. 61

    Wichterle H, Gifford D, Mazzoni E . Mapping neuronal diversity one cell at a time. Science 2013; 341: 725–726.

    Article  Google Scholar 

  62. 62

    Markram H, Muller E, Ramaswamy S, Reimann MW, Abdellah M, Sanchez CA et al. Reconstruction and simulation of neocortical microcircuitry. Cell 2015; 163: 456–492.

    CAS  Article  Google Scholar 

  63. 63

    DeFelipe J, López-Cruz PL, Benavides-Piccione R, Bielza C, Larrañaga P, Anderson S et al. New insights into the classification and nomenclature of cortical GABAergic interneurons. Nat Rev Neurosci 2013; 14: 202–216.

    CAS  Article  Google Scholar 

  64. 64

    Gupta A, Wang Y, Markram H . Organizing principles for a diversity of GABAergic interneurons and synapses in the neocortex. Science 2000; 287: 273–278.

    CAS  Article  Google Scholar 

  65. 65

    Bardy C, Alonso M, Bouthour W, Lledo P-MM . How, when, and where new inhibitory neurons release neurotransmitters in the adult olfactory bulb. J Neurosci 2010; 30: 17023–17034.

    CAS  Article  Google Scholar 

  66. 66

    Carleton A, Petreanu LT, Lansford R, Alvarez-Buylla A, Lledo P-MM . Becoming a new neuron in the adult olfactory bulb. Nat Neurosci 2003; 6: 507–518.

    CAS  Article  Google Scholar 

  67. 67

    Markram H, Toledo-Rodriguez M, Wang Y, Gupta A, Silberberg G, Wu C . Interneurons of the neocortical inhibitory system. Nat Rev Neurosci 2004; 5: 793–807.

    CAS  Article  Google Scholar 

  68. 68

    Ascoli GA, Alonso-Nanclares L, Anderson SA, Barrionuevo G, Benavides-Piccione R, Burkhalter A et al. Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex. Nat Rev Neurosci 2008; 9: 557–568.

    CAS  Article  Google Scholar 

  69. 69

    Druckmann S, Hill S, Schurmann F, Markram H, Segev I . A hierarchical structure of cortical interneuron electrical diversity revealed by automated statistical analysis. Cerebral Cortex 2013; 23: 2994–3006.

    Article  Google Scholar 

  70. 70

    Tasic B, Menon V, Nguyen TN, Kim T-K, Jarsky T, Yao Z et al. Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat Neurosci 2016; 19: 335–346.

    CAS  Article  Google Scholar 

  71. 71

    Hawrylycz M, Miller JA, Menon V, Feng D, Dolbeare T, Guillozet-Bongaarts AL et al. Canonical genetic signatures of the adult human brain. Nat Neurosci 2015; 18: 1832–1844.

    CAS  Article  Google Scholar 

  72. 72

    Stein JL, la Torre-Ubieta de L, Tian Y, Parikshak NN, Hernández IA, Marchetto MC et al. A quantitative framework to evaluate modeling of cortical development by neural stem cells. Neuron 2014; 83: 69–86.

    CAS  Article  Google Scholar 

  73. 73

    McConnell MJ, Lindberg MR, Brennand KJ, Piper JC, Voet T, Cowing-Zitron C et al. Mosaic copy number variation in human neurons. Science 2013; 342: 632–637.

    CAS  Article  Google Scholar 

  74. 74

    Bellin M, Marchetto MC, Gage FH, Mummery CL . Induced pluripotent stem cells: the new patient? Nat Rev Mol Cell Biol 2012; 13: 713–726.

    Article  Google Scholar 

  75. 75

    Marchetto MC, Brennand KJ, Boyer LF, Gage FH . Induced pluripotent stem cells (iPSCs) and neurological disease modeling: progress and promises. Hum Mol Genet 2011; 20: R109–R115.

    CAS  Article  Google Scholar 

  76. 76

    Paşca SP, Portmann T, Voineagu I, Yazawa M, Shcheglovitov A, Paşca AM et al. Using iPSC-derived neurons to uncover cellular phenotypes associated with Timothy syndrome. Nat Med 2011; 17: 1657–1662.

    Article  Google Scholar 

  77. 77

    Yu DX, Marchetto MC, Gage FH . Therapeutic translation of iPSCs for treating neurological disease. Stem Cell 2013; 12: 678–688.

    CAS  Google Scholar 

  78. 78

    Marchetto MC, Carromeu C, Acab A, Yu D, Yeo GW, Mu Y et al. A model for neural development and treatment of Rett syndrome using human induced pluripotent stem cells. Cell 2010; 143: 527–539.

    CAS  Article  Google Scholar 

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Acknowledgements

We are grateful to Elisabeth Santo and Sarah Marshall for help with the morphological reconstruction. We thank Gage lab members Bobbie Miller and Lynne Moore for preparation of viral vectors and Eunice Meija for immunohistochemistry. Thanks to Gage lab (Prattap Venepalli, Apua Paquola, Sara Linker, Son Pham) and Yeo lab (Olga Botvinnik) members for fruitful bioinformatics discussions on single-cell transcriptomics. We thank Mary Lynn Gage for edits on the manuscript. This study was supported by grants from Ipsen Pharma, Annette C. Merle-Smith, The Leona M. and Harry B. Helmsley Charitable Trust Grant #2012-PG-MED002, Bob and Mary Jane Engman, the JPB Foundation, G Harold and Leila Y. Mathers Foundation, and NIH Grants MH095741 (to F.H.G.); also by a Fay/Frank Seed Grant from the Brain Research Foundation and NIH Grants NS075449, HG004659, HG007005 (to G.W.Y.). G.W.Y. is an Alfred P Sloan Research Fellow. This work was also supported by NSF Graduate Research Fellowship (to B.K.), the George E. Hewitt Foundation for Medical Research (to J.E.) the EMBO Long-term fellowship, the Bettencourt Schueller Foundation and the Philippe Foundation (B.N.J.) and the FP7 Marie Curie International Outgoing Fellowship for Career Development (to C.B.).

Author contributions

CB designed and analyzed all experiments and wrote the manuscript with input from GWY and FHG. MVDH and JE prepared the single-cell cDNA libraries and performed the cDNA QC. CB and BK analyzed the single-cell transcriptome data. BNJ, JB, AP and CB performed the FACS experiments. CB, MG, RVH and CM performed the patch-clamping experiments. TE, AP and CB performed the tissue culture. MK and AKB reconstructed the neuronal morphology. RJ designed the viral vector constructs.

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Correspondence to C Bardy or G W Yeo or F H Gage.

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Bardy, C., van den Hurk, M., Kakaradov, B. et al. Predicting the functional states of human iPSC-derived neurons with single-cell RNA-seq and electrophysiology. Mol Psychiatry 21, 1573–1588 (2016). https://doi.org/10.1038/mp.2016.158

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