A Systems Biology Approach Identifies Hidden Regulatory Connections Between the Circadian and Cell-Cycle Checkpoints.

checkpoint signaling circadian rhythms clock genes mathematical modeling p53 systematic approach tumor suppressor

Journal

Frontiers in physiology
ISSN: 1664-042X
Titre abrégé: Front Physiol
Pays: Switzerland
ID NLM: 101549006

Informations de publication

Date de publication:
2020
Historique:
received: 03 02 2020
accepted: 20 03 2020
entrez: 7 5 2020
pubmed: 7 5 2020
medline: 7 5 2020
Statut: epublish

Résumé

Circadian rhythms form a self-sustaining, endogenous, time-keeping system that allows organisms to anticipate daily environmental changes. The core of the clock network consists of interlocking transcriptional-translational feedback loops that ensures that metabolic, behavioral, and physiological processes run on a 24 h timescale. The hierarchical nature of the clock manifests itself in multiple points of control on the daily cell division cycle, which relies on synthesis, degradation, and post-translational modification for progression. This relationship is particularly important for understanding the role of clock components in sensing stress conditions and triggering checkpoint signals that stop cell cycle progression. A case in point is the interplay among the circadian factor PERIOD2 (PER2), the tumor suppressor p53, and the oncogenic mouse double minute-2 homolog protein (MDM2), which is the p53's negative regulator. Under unstressed conditions, PER2 and p53 form a stable complex in the cytosol and, along with MDM2, a trimeric complex in the nucleus. Association of PER2 to the C-terminus end of p53 prevents MDM2-mediated ubiquitylation and degradation of p53 as well as p53's transcriptional activation. Remarkably, when not bound to p53, PER2 acts as substrate for the E3-ligase activity of MDM2; thus, PER2 is degraded in a phosphorylation-independent fashion. Unexpectedly, the phase relationship between PER2 and p53 are opposite; however, a systematic modeling approach, inferred from the oscillatory time course data of PER2 and p53, aided in identifying additional regulatory scenarios that explained,

Identifiants

pubmed: 32372973
doi: 10.3389/fphys.2020.00327
pmc: PMC7176909
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

327

Informations de copyright

Copyright © 2020 Zou, Kim, Gotoh, Liu, Kim and Finkielstein.

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Auteurs

Xianlin Zou (X)

Integrated Cellular Responses Laboratory, Department of Biological Sciences, Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA, United States.

Dae Wook Kim (DW)

Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon, South Korea.

Tetsuya Gotoh (T)

Integrated Cellular Responses Laboratory, Department of Biological Sciences, Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA, United States.

Jingjing Liu (J)

Integrated Cellular Responses Laboratory, Department of Biological Sciences, Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA, United States.

Jae Kyoung Kim (JK)

Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon, South Korea.

Carla V Finkielstein (CV)

Integrated Cellular Responses Laboratory, Department of Biological Sciences, Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA, United States.

Classifications MeSH