A Unified Model for Entrainment by Circadian Clocks: Dynamic Circadian Integrated Response Characteristic (dCiRC).

CiRC Neurospora crassa entrainment mathematical modeling non-parametric model parametric model

Journal

Journal of biological rhythms
ISSN: 1552-4531
Titre abrégé: J Biol Rhythms
Pays: United States
ID NLM: 8700115

Informations de publication

Date de publication:
04 2022
Historique:
pubmed: 15 2 2022
medline: 15 4 2022
entrez: 14 2 2022
Statut: ppublish

Résumé

Circadian rhythms are ubiquitous and are observed in all biological kingdoms. In nature, their primary characteristic or phenotype is the phase of entrainment. There are two main hypotheses related to how circadian clocks entrain, parametric and non-parametric models. The parametric model focuses on the gradual changes of the clock parameters in response to the changing ambient condition, whereas the non-parametric model focuses on the instantaneous change of the phase of the clock in response to the zeitgeber. There are ample empirical data supporting both models. However, only recently has a unifying model been proposed, the circadian integrated response characteristic (CiRC). In the current study, we developed a system of ordinary differential equations, dynamic CiRC (dCiRC), that describes parameters of circadian rhythms and predicts the phase of entrainment in zeitgeber cycles. dCiRC mathematically extracts the underlying information of velocity changes of the internal clock that reflects the parametric model and the phase shift trajectory that reflects the non-parametric model from phase data under entraining conditions. As a proof of concept, we measured clock parameters of 26

Identifiants

pubmed: 35156426
doi: 10.1177/07487304211069454
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

202-215

Auteurs

Zheming An (Z)

Department of Mathematics, Rutgers-The State University of New Jersey, Camden, New Jersey, USA.
Center for Computational and Integrative Biology, Rutgers-The State University of New Jersey, Camden, New Jersey, USA.

Benedetto Piccoli (B)

Department of Mathematics, Rutgers-The State University of New Jersey, Camden, New Jersey, USA.
Center for Computational and Integrative Biology, Rutgers-The State University of New Jersey, Camden, New Jersey, USA.

Martha Merrow (M)

Institute of Medical Psychology, Faculty of Medicine, LMU Munich, Munich, Germany.

Kwangwon Lee (K)

Center for Computational and Integrative Biology, Rutgers-The State University of New Jersey, Camden, New Jersey, USA.
Department of Biology, Rutgers-The State University of New Jersey, Camden, New Jersey, USA.

Articles similaires

Fragaria Light Plant Leaves Osmosis Stress, Physiological
Humans Circadian Rhythm Adult Aged Aging

Classifications MeSH