Molecular, anatomical, and functional organization of lung interoceptors
Liu, Y.; Kinsey, L.; Diaz de Arce, A. J.; Krasnow, M. A.
Show abstract
Interoceptors, sensory neurons that monitor internal organs and physiological states, are essential for regulating physiology, shaping behavior, and generating internal perceptions. Here, we present a comprehensive transcriptomic atlas of mouse lung interoceptors, identifying 10 molecular subtypes. These subtypes differ in developmental origin, sensory receptor repertoire, signaling molecules, anatomical receptive fields, terminal morphologies, and cell contacts. Activity recordings and functional interrogation of two Piezo2+ subtypes revealed distinct sensory properties and separate roles in breathing control: one regulates inspiratory time; the other regulates inspiratory flow. Together, these findings suggest that this pronounced cellular diversity of lung interoceptors enables the system to encode diverse and dynamic sensory information, mediate myriad local cellular interactions, and regulate respiratory physiology with precision.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- A cholinergic spinal pathway for the adaptive control of breathing 96%
- Phox2a defines a developmental origin of the anterolateral system in mice and humans 96%
- Prepronociceptin expressing neurons in the extended amygdala encode and promote rapid arousal responses to motivationally salient stimuli 95%
Similar papers in this journal
- Mechanoreceptor signal convergence and transformation in the dorsal horn flexibly shape a diversity of outputs to the brain 97%
- A human fetal lung cell atlas uncovers proximal-distal gradients of differentiation and key regulators of epithelial fates 96%
- Molecular topography of an entire nervous system 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.