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Defining Selective Neuronal Resilience and Identifying Targets for Neuroprotection and Axon Regeneration Using Single-Cell RNA Sequencing: Experimental Approaches

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Axon Regeneration

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2636))

Abstract

A prevalent feature among neurodegenerative conditions, including axonal injury, is that certain neuronal types are disproportionately affected, while others are more resilient. Identifying molecular features that separate resilient from susceptible populations could reveal potential targets for neuroprotection and axon regeneration. A powerful approach to resolve molecular differences across cell types is single-cell RNA-sequencing (scRNA-seq). scRNA-seq is a robustly scalable approach that enables the parallel sampling of gene expression across many individual cells. Here we present a systematic framework to apply scRNA-seq to track neuronal survival and gene expression changes following axonal injury. Our methods utilize the mouse retina because it is an experimentally accessible central nervous system tissue and its cell types have been comprehensively characterized by scRNA-seq. This chapter will focus on preparing retinal ganglion cells (RGCs) for scRNA-seq and pre-processing of sequencing results.

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References

  1. Maclaren RE, Taylor JSH (1997) Regeneration in the developing optic nerve: correlating observations in the opossum to other mammalian systems. Prog Neurobiol 53:381–398

    Article  CAS  PubMed  Google Scholar 

  2. Moore DL, Goldberg JL (2011) Multiple transcription factor families regulate axon growth and regeneration. Dev Neurobiol 71:1186–1211. https://doi.org/10.1002/dneu.20934

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Goldberg JL, Klassen MP, Hua Y, Barres BA (2002) Amacrine-signaled loss of intrinsic axon growth ability by retinal ganglion cells. Science 80(296):1860–1864. https://doi.org/10.1126/science.1068428

    Article  Google Scholar 

  4. Rau A, Dhara SP, Udvadia AJ, Auer PL (2019) Regeneration Rosetta: an interactive web application to explore regeneration-associated gene expression and chromatin accessibility. G3 Genes Genomes Genet 9:3953–3959. https://doi.org/10.1534/g3.119.400729

    Article  CAS  Google Scholar 

  5. Dhara SP, Rau A, Flister MJ et al (2019) Cellular reprogramming for successful CNS axon regeneration is driven by a temporally changing cast of transcription factors. Sci Rep 9:1–12. https://doi.org/10.1038/s41598-019-50485-6

    Article  CAS  Google Scholar 

  6. Kizil C, Kaslin J, Kroehne V, Brand M (2012) Adult neurogenesis and brain regeneration in zebrafish. Dev Neurobiol 72:429–461. https://doi.org/10.1002/dneu.20918

    Article  PubMed  Google Scholar 

  7. Van houcke J, Bollaerts I, Geeraerts E et al (2017) Successful optic nerve regeneration in the senescent zebrafish despite age-related decline of cell intrinsic and extrinsic response processes. Neurobiol Aging 60:1–10. https://doi.org/10.1016/j.neurobiolaging.2017.08.013

    Article  CAS  PubMed  Google Scholar 

  8. Macosko EZ, Basu A, Satija R et al (2015) Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161:1202–1214. https://doi.org/10.1016/j.cell.2015.05.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Shekhar K, Lapan SW, Whitney IE et al (2016) Comprehensive classification of retinal bipolar neurons by single-cell transcriptomics. Cell 166:1308–1323.e30. https://doi.org/10.1016/j.cell.2016.07.054

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Tran NM, Shekhar K, Whitney IE et al (2019) Single-cell profiles of retinal ganglion cells differing in resilience to injury reveal neuroprotective genes. Neuron 104:1039–1055.e12. https://doi.org/10.1016/j.neuron.2019.11.006

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yan W, Laboulaye MA, Tran NM et al (2020) Mouse retinal cell atlas: molecular identification of over sixty Amacrine cell types. J Neurosci 40:5177–5195. https://doi.org/10.1523/JNEUROSCI.0471-20.2020

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Rheaume BA, Jereen A, Bolisetty M et al (2018) Single cell transcriptome profiling of retinal ganglion cells identifies cellular subtypes. Nat Commun 9:2759. https://doi.org/10.1038/s41467-018-05134-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Yao Z, Nguyen TN, van Velthoven C et al (2020) A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation. bioRxiv:2020.03.30.015214. https://doi.org/10.1101/2020.03.30.015214

  14. Tasic B, Yao Z, Graybuck LT et al (2018) Shared and distinct transcriptomic cell types across neocortical areas. Nature 563:72–78. https://doi.org/10.1038/s41586-018-0654-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Zeisel A, Hochgerner H, Lönnerberg P et al (2018) Molecular architecture of the mouse nervous system. Cell 174:999–1014.e22. https://doi.org/10.1016/J.CELL.2018.06.021

    Article  PubMed  PubMed Central  Google Scholar 

  16. Saunders A, Macosko EZ, Wysoker A et al (2018) Molecular diversity and specializations among the cells of the adult mouse brain. Cell 174:1015–1030.e16. https://doi.org/10.1016/j.cell.2018.07.028

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kaplan A, Spiller KJ, Towne C et al (2014) Neuronal matrix metalloproteinase-9 is a determinant of selective neurodegeneration. Neuron 81:333–348. https://doi.org/10.1016/J.NEURON.2013.12.009

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Bray ER, Yungher BJ, Levay K et al (2019) Thrombospondin-1 mediates axon regeneration in retinal ganglion cells. Neuron 103:642–657.e7. https://doi.org/10.1016/j.neuron.2019.05.044

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Duan X, Qiao M, Bei F et al (2015) Subtype-specific regeneration of retinal ganglion cells following axotomy: effects of osteopontin and mTOR signaling. Neuron 85:1244–1256. https://doi.org/10.1016/j.neuron.2015.02.017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Butrus S, Sagireddy S, Yan W SK (2021) Defining selective neuronal resilience and identifying targets of neuroprotection and axon regeneration using single-cell RNA sequencing – computational Approaches. In: Methods in molecular biology. Humana Press Inc., Totowa

    Google Scholar 

  21. Tang Z, Zhang S, Lee C et al (2011) An optic nerve crush injury murine model to study retinal ganglion cell survival. J Vis Exp 2685. https://doi.org/10.3791/2685

  22. Cameron E, Xia X, Galvao J et al (2020) Optic nerve crush in mice to study retinal ganglion cell survival and regeneration. Bioanalysis 10. https://doi.org/10.21769/bioprotoc.3559

  23. Galindo-Romero C, Avilés-Trigueros M, Jiménez-López M et al (2011) Axotomy-induced retinal ganglion cell death in adult mice: quantitative and topographic time course analyses. Exp Eye Res 92:377–387. https://doi.org/10.1016/j.exer.2011.02.008

    Article  CAS  PubMed  Google Scholar 

  24. PĂ©rez de Sevilla MĂĽller L, Sargoy A, Rodriguez AR, Brecha NC (2014) Melanopsin ganglion cells are the most resistant retinal ganglion cell type to axonal injury in the rat retina. PLoS One 9:e93274. https://doi.org/10.1371/journal.pone.0093274

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Yang S-G, Li C-P, Peng X-Q et al (2020) Strategies to promote long-distance optic nerve regeneration. Front Cell Neurosci 14:119. https://doi.org/10.3389/fncel.2020.00119

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Mahar M, Cavalli V (2018) Intrinsic mechanisms of neuronal axon regeneration. Nat Rev Neurosci 19:323–337

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. He Z, Jin Y (2016) Intrinsic control of axon regeneration. Neuron 90:437–451

    Article  CAS  PubMed  Google Scholar 

  28. Jeon CJ, Strettoi E, Masland RH (1998) The major cell populations of the mouse retina. J Neurosci 18:8936–8946

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Klein AM, Mazutis L, Akartuna I et al (2015) Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161:1187–1201. https://doi.org/10.1016/j.cell.2015.04.044

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Picelli S, Faridani OR, Björklund ÅK et al (2014) Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc 9:171–181. https://doi.org/10.1038/nprot.2014.006

    Article  CAS  PubMed  Google Scholar 

  31. Vong L, Ye C, Yang Z et al (2011) Leptin action on GABAergic neurons prevents obesity and reduces inhibitory tone to POMC neurons. Neuron 71:142–154. https://doi.org/10.1016/j.neuron.2011.05.028

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Buffelli M, Burgess RW, Feng G et al (2003) Genetic evidence that relative synaptic efficacy biases the outcome of synaptic competition. Nature 424:430–434. https://doi.org/10.1038/nature01844

    Article  CAS  PubMed  Google Scholar 

  33. Wu YE, Pan L, Zuo Y et al (2017) Detecting activated cell populations using single-cell RNA-seq. Neuron 96:313–329.e6. https://doi.org/10.1016/J.NEURON.2017.09.026

    Article  PubMed  Google Scholar 

  34. Hrvatin S, Hochbaum DR, Nagy MA et al (2018) Single-cell analysis of experience-dependent transcriptomic states in the mouse visual cortex. Nat Neurosci 21:120–129. https://doi.org/10.1038/s41593-017-0029-5

    Article  CAS  PubMed  Google Scholar 

  35. Hwang B, Lee JH, Bang D (2018) Single-cell RNA sequencing technologies and bioinformatics pipelines. Exp Mol Med 50:96

    Article  PubMed  PubMed Central  Google Scholar 

  36. Chen G, Ning B, Shi T (2019) Single-cell RNA-seq technologies and related computational data analysis. Front Genet 10:317

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Villani AC, Shekhar K (2017) Single-cell RNA sequencing of human T cells. In: Methods in molecular biology. Humana Press Inc., Totowa, pp 203–239

    Google Scholar 

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Acknowledgments

We would like to thank Drs. Joshua Sanes and Zhigang He for their mentorship, guidance, and support. We thank Drs. Inbal Benhar and Irene Whitney for their invaluable contributions to the development of retinal cell collection protocols. We also thank Salwan Butrus and Drs. Wenjun Yan and Karthik Shekhar for their critical reading and feedback on this manuscript.

Funding

This work was supported by EY029360 (NIH, NEI) to N.M.T. and Wings for Life Spinal Cord Research Foundation to A.J.

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Correspondence to Nicholas M. Tran .

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Jacobi, A., Tran, N.M. (2023). Defining Selective Neuronal Resilience and Identifying Targets for Neuroprotection and Axon Regeneration Using Single-Cell RNA Sequencing: Experimental Approaches. In: Udvadia, A.J., Antczak, J.B. (eds) Axon Regeneration. Methods in Molecular Biology, vol 2636. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3012-9_1

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  • DOI: https://doi.org/10.1007/978-1-0716-3012-9_1

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3011-2

  • Online ISBN: 978-1-0716-3012-9

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