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The transcription factor unc-130/FOXD3/4 contributes to the biphasic calcium response required to optimize avoidance behavior

The central neural network optimizes avoidance behavior depending on the nociceptive stimulation intensity and is essential for survival. How the property of hub neurons that enables the selection of behaviors is genetically defined is not well understood. We show that the transcription factor unc-1...

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Detalles Bibliográficos
Autores principales: Hori, Sayaka, Mitani, Shohei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8814005/
https://www.ncbi.nlm.nih.gov/pubmed/35115609
http://dx.doi.org/10.1038/s41598-022-05942-0
Descripción
Sumario:The central neural network optimizes avoidance behavior depending on the nociceptive stimulation intensity and is essential for survival. How the property of hub neurons that enables the selection of behaviors is genetically defined is not well understood. We show that the transcription factor unc-130, a human FOXD3/4 ortholog, is required to optimize avoidance behavior depending on stimulus strength in Caenorhabditis elegans. unc-130 is necessary for both ON responses (calcium decreases) and OFF responses (calcium increases) in AIBs, central neurons of avoidance optimization. Ablation of predicted upstream inhibitory neurons reduces the frequency of turn behavior, suggesting that optimization needs both calcium responses. At the molecular level, unc-130 upregulates the expression of at least three genes: nca-2, a homolog of the vertebrate cation leak channel NALCN; glr-1, an AMPA-type glutamate receptor; and eat-4, a hypothetical L-glutamate transmembrane transporter in the central neurons of optimization. unc-130 shows more limited regulation in optimizing behavior than an atonal homolog lin-32, and unc-130 and lin-32 appear to act in parallel molecular pathways. Our findings suggest that unc-130 is required for the establishment of some AIB identities to optimize avoidance behavior.