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 PMID:38530893  

Feedforward and feedback mechanisms cooperatively regulate rapid experience-dependent response adaptation in a single thermosensory neuron type.

Tyler J Hill | Piali Sengupta
Proceedings of the National Academy of Sciences of the United States of America | 2024

Sensory adaptation allows neurons to adjust their sensitivity and responses based on recent experience. The mechanisms that mediate continuous adaptation to stimulus history over seconds- to hours-long timescales, and whether these mechanisms can operate within a single sensory neuron type, are unclear. The single pair of AFD thermosensory neurons in Caenorhabditis elegans exhibits experience-dependent plasticity in their temperature response thresholds on both minutes- and hours-long timescales upon a temperature upshift. While long-term response adaptation requires changes in gene expression in AFD, the mechanisms driving rapid response plasticity are unknown. Here, we show that rapid thermosensory response adaptation in AFD is mediated via cGMP and calcium-dependent feedforward and feedback mechanisms operating at the level of primary thermotransduction. We find that either of two thermosensor receptor guanylyl cyclases (rGCs) alone is sufficient to drive rapid adaptation, but that each rGC drives adaptation at different rates. rGC-driven adaptation is mediated in part via phosphorylation of their intracellular domains, and calcium-dependent feedback regulation of basal cGMP levels via a neuronal calcium sensor protein. In turn, cGMP levels feedforward via cGMP-dependent protein kinases to phosphorylate a specific subunit of the cGMP-gated thermotransduction channel to further regulate rapid adaptation. Our results identify multiple molecular pathways that act in AFD to ensure rapid adaptation to a temperature change and indicate that the deployment of both transcriptional and nontranscriptional mechanisms within a single sensory neuron type can contribute to continuous sensory adaptation.

Pubmed ID: 38530893

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Associated grants

  • Agency: NIGMS NIH HHS, United States
    Id: R35 GM122463

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Statistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.

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