bioRxivNeurosciencePreprint
Parabrachial bombesin receptor subtype 3 neurons facilitate heat hypersensitivity in persistent pain
Heather N. AlleniD, Erick Josué Rodríguez-PalmaiD, Tyler S. NelsoniD, Naomi K Grabus, Nia A Dufeal, Rajesh KhannaiD
Abstract
The parabrachial nucleus (PBN) is a critical hub for pain processing that acts as a switchboard for nociceptive signals, relaying sensory information to forebrain regions that integrate the sensory and affective dimensions of pain. Although the PBN is well established as a key regulator of pain, the remarkable heterogeneity of its neuronal populations has hindered efforts to identify specific cell types responsible for distinct aspects of pain processing. Here, we identify bombesin receptor subtype 3 (Brs3)-expressing neurons as a distinct glutamatergic PBN subpopulation involved in heat hypersensitivity associated with persistent pain. Using Fos expression analysis and in vivo calcium imaging, we demonstrate that Brs3 neurons exhibit heightened activity in response to heat stimulation following an inflammatory insult or neuropathic injury. Inhibition of Brs3 neurons effectively reduces heat, but not mechanical, hypersensitivity induced by both inflammatory and neuropathic pain, suggesting a specific role in processing heat hypersensitivity. Ablation of parabrachial Brs3 neurons prior to induction of pain also selectively prevents the development of heat hypersensitivity induced by persistent inflammation in mice. Brs3-expressing neurons encompass multiple previously identified pain-related PBN subpopulations, including those expressing the mu opioid receptor (Oprm1), tachykinin 1 receptor (Tacr1), and neuropeptide Y Y1 receptor (Npy1r), positioning Brs3 as a potential unifying marker of heat hypersensitivity circuits. These findings provide new insight into the organization of pain-processing networks in the PBN and highlight Brs3 neurons as a crucial population for heat pain.
- organism: mouse
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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