@article {Fang7425, author = {Xin Fang and Laiche Djouhri and Joel A. Black and Sulayman D. Dib-Hajj and Stephen G. Waxman and Sally N. Lawson}, title = {The Presence and Role of the Tetrodotoxin-Resistant Sodium Channel Nav1.9 (NaN) in Nociceptive Primary Afferent Neurons}, volume = {22}, number = {17}, pages = {7425--7433}, year = {2002}, doi = {10.1523/JNEUROSCI.22-17-07425.2002}, publisher = {Society for Neuroscience}, abstract = {This is the first examination of sensory receptive properties and associated electrophysiological properties in vivo of dorsal root ganglion (DRG) neurons that express the TTX-resistant sodium channel Nav1.9 (NaN). Intracellular recordings in lumbar DRGs in Wistar rats enabled units with dorsal root C-, Aδ-, or Aα/β-fibers to be classified as nociceptive, low-threshold mechanoreceptive (LTM), or unresponsive. Intracellular dye injection enabled subsequent immunocytochemistry for Nav1.9-like immunoreactivity (Nav1.9-LI).Nav1.9-LI was expressed selectively in nociceptive-type (C- and A-fiber nociceptive and C-unresponsive) units. Of the nociceptive units, 64, 54, and 31\% of C-, Aδ-, and Aα/β-fiber units, respectively, were positive for Nav1.9-LI. C-unresponsive units were included in the nociceptive-type group on the basis of their nociceptor-like membrane properties; 91\% were positive. Nav1.9-LI was undetectable in Aδ- or Aα/β-fiber LTM units and in one C-LTM unit. Nav1.9-LI intensity was correlated negatively with soma size and conduction velocity in nociceptive units and with conduction velocity in C-fiber units. There was a positive correlation with action potential rise time in nociceptive-type units with membrane potentials equal to or more negative than {\textendash}50 mV. The data provide direct evidence that Nav1.9 is expressed selectively in (but not in all) C- and A-fiber nociceptive-type units and suggest that Nav1.9 contributes to membrane properties that are typical of nociceptive neurons.}, issn = {0270-6474}, URL = {https://www.jneurosci.org/content/22/17/7425}, eprint = {https://www.jneurosci.org/content/22/17/7425.full.pdf}, journal = {Journal of Neuroscience} }