Daily electrical activity in the master circadian clock of a diurnal mammal
dc.contributor.author | Bano-Otalora, B | |
dc.contributor.author | Moye, MJ | |
dc.contributor.author | Brown, T | |
dc.contributor.author | Lucas, RJ | |
dc.contributor.author | Diekman, CO | |
dc.contributor.author | Belle, MD | |
dc.date.accessioned | 2021-12-13T10:47:27Z | |
dc.date.issued | 2021-11-30 | |
dc.date.updated | 2021-12-11T02:00:13Z | |
dc.description.abstract | Circadian rhythms in mammals are orchestrated by a central clock within the suprachiasmatic nuclei (SCN). Our understanding of the electrophysiological basis of SCN activity comes overwhelmingly from a small number of nocturnal rodent species, and the extent to which these are retained in day-active animals remains unclear. Here, we recorded the spontaneous and evoked electrical activity of single SCN neurons in the diurnal rodent Rhabdomys pumilio, and developed cutting-edge data assimilation and mathematical modeling approaches to uncover the underlying ionic mechanisms. As in nocturnal rodents, R. pumilio SCN neurons were more excited during daytime hours. By contrast, the evoked activity of R. pumilio neurons included a prominent suppressive response that is not present in the SCN of nocturnal rodents. Our modeling revealed and subsequent experiments confirmed transient subthreshold A-type potassium channels as the primary determinant of this response, and suggest a key role for this ionic mechanism in optimizing SCN function to accommodate R. pumilio's diurnal niche. | en_GB |
dc.description.sponsorship | Biotechnology and Biological Sciences Research Council (BBSRC) | en_GB |
dc.description.sponsorship | Wellcome Trust | en_GB |
dc.description.sponsorship | National Science Foundation (NSF) | en_GB |
dc.description.sponsorship | Army Research Office | en_GB |
dc.description.sponsorship | US-UK Fulbright Commission | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.format.extent | e68179- | |
dc.identifier.citation | Vol. 10, article e68179 | en_GB |
dc.identifier.doi | https://doi.org/10.7554/eLife.68179 | |
dc.identifier.grantnumber | BB/P009182/1 | en_GB |
dc.identifier.grantnumber | BB/S01764X/1 | en_GB |
dc.identifier.grantnumber | BB/N014901/1 | en_GB |
dc.identifier.grantnumber | 210684/Z/18/Z | en_GB |
dc.identifier.grantnumber | DMS 155237 | en_GB |
dc.identifier.grantnumber | W911NF-16-1-0584 | en_GB |
dc.identifier.grantnumber | EP/N014391/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/128112 | |
dc.identifier | ORCID: 0000-0002-4917-957X (Belle, Mino Dc) | |
dc.language.iso | en | en_GB |
dc.publisher | eLife Sciences Publications | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/34845984 | en_GB |
dc.relation.url | http://modeldb.yale.edu/267183 | en_GB |
dc.relation.url | https://github.com/mattmoye/neuroDA | en_GB |
dc.rights | © 2021, Bano-Otalora et al. Open access. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited. | en_GB |
dc.subject | circadian rhythms | en_GB |
dc.subject | computational biology | en_GB |
dc.subject | diurnality | en_GB |
dc.subject | electrical activity | en_GB |
dc.subject | mathematical modelling | en_GB |
dc.subject | neuroscience | en_GB |
dc.subject | suprachiasmatic nucleus | en_GB |
dc.subject | systems biology | en_GB |
dc.title | Daily electrical activity in the master circadian clock of a diurnal mammal | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2021-12-13T10:47:27Z | |
dc.identifier.issn | 2050-084X | |
exeter.article-number | ARTN e68179 | |
exeter.place-of-publication | England | |
dc.description | This is the final version. Available on open access from eLife Sciences Publications via the DOI in this record | en_GB |
dc.description | Data availability: All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 2, 3 and 6. Code for simulating our conductance-based models is available in ModelDB (McDougal et al 2017, J Comput Neurosci) at http://modeldb.yale.edu/267183. Code for performing neuronal data assimilation (neuroDA) to infer model parameters from current-clamp recordings is available at https://github.com/mattmoye/neuroDA; copy archived at https://archive.softwareheritage.org/swh:1:rev:faf27e9035c28320feb2f82c37bd2bb8e0fc0fbd. | en_GB |
dc.identifier.eissn | 2050-084X | |
dc.identifier.journal | eLife | en_GB |
dc.relation.ispartof | Elife, 10 | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2021-10-09 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2021-11-30 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2021-12-13T09:26:40Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2021-12-13T10:47:31Z | |
refterms.panel | A | en_GB |
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This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.