Skip to main content
SpringerLink
Log in

Channelrhodopsin-2 Assisted Circuit Mapping in the Spinal Cord Dorsal Horn

  • Protocol
  • First Online:
Contemporary Approaches to the Study of Pain

Part of the book series: Neuromethods ((NM,volume 178))

Abstract

Identifying how neural networks communicate through the organization of microcircuits in the central nervous system is a long-standing challenge in neuroscience. Collecting this information in areas that lack clear cellular organization such as the dorsal horn of the spinal cord, where heterogeneous populations of cells are intermingled, has been especially difficult. Improvements in optical technologies in combination with advanced genetic techniques, collectively termed optogenetics, have greatly improved our ability to address this issue. Several studies have now employed optogenetics to study the connectivity of various dorsal horn interneuron populations, as well as modality-specific input provided by primary afferent populations. This work allows for a circuit-based understanding of spinal sensory processing mechanisms to be assembled, something that has been sought since the publication of the gate control theory in 1965. This chapter seeks to provide a practical, experimental-based description of the various optogenetic approaches available to characterize dorsal horn circuits at a level of resolution not possible using more classical approaches.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 299.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Koch SC, Acton D, Goulding M (2018) Spinal circuits for touch, pain, and itch. Annu Rev Physiol 80:189–217

    Article  CAS  PubMed  Google Scholar 

  2. Moehring F et al (2018) Uncovering the cells and circuits of touch in Normal and pathological settings. Neuron 100(2):349–360

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Peirs C, Seal RP (2016) Neural circuits for pain: recent advances and current views. Science 354(6312):578–584

    Article  CAS  PubMed  Google Scholar 

  4. Todd AJ (2010) Neuronal circuitry for pain processing in the dorsal horn. Nat Rev Neurosci 11(12):823–836

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Graham BA, Brichta AM, Callister RJ (2007) Moving from an averaged to specific view of spinal cord pain processing circuits. J Neurophysiol 98(3):1057–1063

    Article  CAS  PubMed  Google Scholar 

  6. Yasaka T et al (2010) Populations of inhibitory and excitatory interneurons in lamina II of the adult rat spinal dorsal horn revealed by a combined electrophysiological and anatomical approach. Pain 151(2):475–488

    Article  PubMed  PubMed Central  Google Scholar 

  7. Browne TJ et al (2020) Transgenic cross-referencing of inhibitory and excitatory interneuron populations to dissect neuronal heterogeneity in the dorsal horn. Front Mol Neurosci 13:32

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Gatto G et al (2019) Neuronal diversity in the somatosensory system: bridging the gap between cell type and function. Curr Opin Neurobiol 56:167–174

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Smith KM et al (2014) The search for novel analgesics: re-examining spinal cord circuits with new tools. Front Pharmacol 5:22

    PubMed  PubMed Central  Google Scholar 

  10. Graham BA, Hughes DI (2019) Rewards, perils and pitfalls of untangling spinal pain circuits. Curr Opin Physio 11:35–41

    Article  Google Scholar 

  11. Häring M et al (2018) Neuronal atlas of the dorsal horn defines its architecture and links sensory input to transcriptional cell types. Nat Neurosci 21(6):869–880

    Article  PubMed  CAS  Google Scholar 

  12. Sathyamurthy A et al (2018) Massively parallel single nucleus transcriptional profiling defines spinal cord neurons and their activity during behavior. Cell Rep 22(8):2216–2225

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Lu Y, Perl ER (2003) A specific inhibitory pathway between substantia gelatinosa neurons receiving direct C-fiber input. J Neurosci 23(25):8752–8758

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Lu Y, Perl ER (2005) Modular organization of excitatory circuits between neurons of the spinal superficial dorsal horn (laminae I and II). J Neurosci 25(15):3900–3907

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Santos SFA et al (2007) Excitatory interneurons dominate sensory processing in the spinal substantia gelatinosa of rat. J Physiol 581(Pt 1):241–254

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kato G et al (2007) Differential wiring of local excitatory and inhibitory synaptic inputs to islet cells in rat spinal lamina II demonstrated by laser scanning photostimulation. J Physiol 580(Pt.3):815–833

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kosugi M et al (2013) Subpopulation-specific patterns of intrinsic connectivity in mouse superficial dorsal horn as revealed by laser scanning photostimulation. J Physiol 591(7):1935–1949

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Callaway EM, Katz LC (1993) Photostimulation using caged glutamate reveals functional circuitry in living brain slices. Proc Natl Acad Sci U S A 90(16):7661–7665

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Boyden ES et al (2005) Millisecond-timescale, genetically targeted optical control of neural activity. Nat Neurosci 8(9):1263–1268

    Article  CAS  PubMed  Google Scholar 

  20. Brown J et al (2018) Expanding the Optogenetics toolkit by topological inversion of Rhodopsins. Cell 175(4):1131–1140.e11

    Article  CAS  PubMed  Google Scholar 

  21. Mattis J et al (2011) Principles for applying optogenetic tools derived from direct comparative analysis of microbial opsins. Nat Methods 9(2):159–172

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Chen IW et al (2019) In vivo submillisecond two-photon Optogenetics with temporally focused patterned light. J Neurosci 39(18):3484–3497

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Wiegert JS et al (2017) Silencing neurons: tools, applications, and experimental constraints. Neuron 95(3):504–529

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Haery L et al (2019) Adeno-associated virus technologies and methods for targeted neuronal manipulation. Front Neuroanat 13:93–93

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Ting JT, Feng G (2013) Development of transgenic animals for optogenetic manipulation of mammalian nervous system function: progress and prospects for behavioral neuroscience. Behav Brain Res 255:3–18

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Madisen L et al (2015) Transgenic mice for intersectional targeting of neural sensors and effectors with high specificity and performance. Neuron 85(5):942–958

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Navabpour S, Kwapis JL, Jarome TJ (2019) A neuroscientist's guide to transgenic mice and other genetic tools. Neurosci Biobehav Rev 108:732–748

    Article  PubMed  PubMed Central  Google Scholar 

  28. Kim H et al (2018) Mouse Cre-LoxP system: general principles to determine tissue-specific roles of target genes. Lab Anim Res 34(4):147–159

    Article  PubMed  PubMed Central  Google Scholar 

  29. Guru A et al (2015) Making sense of Optogenetics. Int J Neuropsychopharmacol 18(11):pyv079-pyv079

    Article  CAS  Google Scholar 

  30. Cordero-Erausquin M et al (2016) Neuronal networks and nociceptive processing in the dorsal horn of the spinal cord. Neuroscience 338:230–247

    Article  CAS  PubMed  Google Scholar 

  31. Snyder LM et al (2018) Kappa opioid receptor distribution and function in primary afferents. Neuron 99(6):1274–1288.e6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Pagani M et al (2019) How gastrin-releasing peptide opens the spinal gate for itch. Neuron 103(1):102–117.e5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Iyer SM et al (2014) Virally mediated optogenetic excitation and inhibition of pain in freely moving nontransgenic mice. Nat Biotechnol 32(3):274–278

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Spencer NJ et al (2018) Visceral pain - novel approaches for optogenetic control of spinal afferents. Brain Res 1693(Pt B):159–164

    Article  CAS  PubMed  Google Scholar 

  35. Zhu M et al (2019) Preparation of acute spinal cord slices for whole-cell patch-clamp recording in substantia Gelatinosa neurons. J Vis Exp 143

    Google Scholar 

  36. Kim J et al (2014) Optogenetic mapping of cerebellar inhibitory circuitry reveals spatially biased coordination of interneurons via electrical synapses. Cell Rep 7(5):1601–1613

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Ting JT et al (2014) Acute brain slice methods for adult and aging animals: application of targeted patch clamp analysis and optogenetics. Methods Mol Biol 1183:221–242

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Carp JS et al (2008) An in vitro protocol for recording from spinal motoneurons of adult rats. J Neurophysiol 100(1):474–481

    Article  PubMed  PubMed Central  Google Scholar 

  39. Leroy F, Lamotte d'Incamps B (2016) The preparation of oblique spinal cord slices for ventral root stimulation. J Vis Exp 116:54525

    Google Scholar 

  40. Segev A, Garcia-Oscos F, Kourrich S (2016) Whole-cell patch-clamp recordings in brain slices. J Vis Exp 112:54024

    Google Scholar 

  41. Wang H, Zylka MJ (2009) Mrgprd-expressing polymodal nociceptive neurons innervate most known classes of substantia gelatinosa neurons. J Neurosci 29(42):13202–13209

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Honsek SD, Seal RP, Sandkuhler J (2015) Presynaptic inhibition of optogenetically identified VGluT3+ sensory fibres by opioids and baclofen. Pain 156(2):243–251

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Tashima R et al (2018) Optogenetic activation of non-nociceptive Abeta fibers induces neuropathic pain-like sensory and emotional behaviors after nerve injury in rats. eNeuro 5(1):ENEURO.0450-17.2018

    Article  PubMed  PubMed Central  Google Scholar 

  44. Albisetti GW et al (2019) Dorsal horn gastrin-releasing peptide expressing neurons transmit spinal itch but not pain signals. J Neurosci 39(12):2238–2250

    Article  PubMed  PubMed Central  Google Scholar 

  45. Hachisuka J et al (2018) Wind-up in lamina I spinoparabrachial neurons: a role for reverberatory circuits. Pain 159(8):1484–1493

    Article  PubMed  PubMed Central  Google Scholar 

  46. Smith KM et al (2019) Calretinin positive neurons form an excitatory amplifier network in the spinal cord dorsal horn. Elife 8:e49190

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Petitjean H et al (2019) Recruitment of Spinoparabrachial neurons by dorsal horn Calretinin neurons. Cell Rep 28(6):1429–1438.e4

    Article  CAS  PubMed  Google Scholar 

  48. Melzack R, Wall PD (1965) Pain mechanisms: a new theory. Science 150(3699):971–979

    Article  CAS  PubMed  Google Scholar 

  49. Foster E et al (2015) Targeted ablation, silencing, and activation establish glycinergic dorsal horn neurons as key components of a spinal gate for pain and itch. Neuron 85(6):1289–1304

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Francois A et al (2017) A brainstem-spinal cord inhibitory circuit for mechanical pain modulation by GABA and Enkephalins. Neuron 93(4):822–839.e6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Acton D et al (2019) Spinal neuropeptide Y1 receptor-expressing neurons form an essential excitatory pathway for mechanical itch. Cell Rep 28(3):625–639.e6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Boyle KA et al (2019) Defining a spinal microcircuit that gates myelinated afferent input: implications for tactile allodynia. Cell Rep 28(2):526–540.e6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Yang K et al (2015) Optoactivation of parvalbumin neurons in the spinal dorsal horn evokes GABA release that is regulated by presynaptic GABAB receptors. Neurosci Lett 594:55–59

    Article  CAS  PubMed  Google Scholar 

  54. Fields HL, Basbaum AI (1978) Brainstem control of spinal pain-transmission neurons. Annu Rev Physiol 40:217–248

    Article  CAS  PubMed  Google Scholar 

  55. Kato G et al (2006) Direct GABAergic and glycinergic inhibition of the substantia gelatinosa from the rostral ventromedial medulla revealed by in vivo patch-clamp analysis in rats. J Neurosci 26(6):1787–1794

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Eccles JC, Schmidt R, Willis WD (1963) Pharmacological studies on presynaptic inhibition. J Physiol 168(3):500–530

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Brooks CM, Koizumi K, Malcolm JL (1955) Effects of changes in temperature on reactions of spinal cord. J Neurophysiol 18(3):205–216

    Article  CAS  PubMed  Google Scholar 

  58. Fink AJP et al (2014) Presynaptic inhibition of spinal sensory feedback ensures smooth movement. Nature 509(7498):43–48

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Pittsburgh Center for Pain Research and Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, USA

    Kelly M. Smith

  2. Brain Neuromodulation Program, Hunter Medial Research Institute and School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia

    Brett A. Graham

Authors
  1. Kelly M. Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Brett A. Graham
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Brett A. Graham .

Editor information

Editors and Affiliations

  1. Department of Neurobiology, Pittsburgh Center for Pain Research, University of Pittsburgh, Pittsburgh, PA, USA

    Rebecca P. Seal

1 Electronic Supplementary Material

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Smith, K.M., Graham, B.A. (2022). Channelrhodopsin-2 Assisted Circuit Mapping in the Spinal Cord Dorsal Horn. In: Seal, R.P. (eds) Contemporary Approaches to the Study of Pain. Neuromethods, vol 178. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2039-7_18

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-2039-7_18

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2038-0

  • Online ISBN: 978-1-0716-2039-7

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation