bims-ciryme Biomed News
on Circadian rhythms and metabolism
Issue of 2020‒08‒16
two papers selected by
Gabriela Da Silva Xavier
University of Birmingham

  1. Neuron. 2020 Aug 04. pii: S0896-6273(20)30529-8. [Epub ahead of print]
    Shan Y, Abel JH, Li Y, Izumo M, Cox KH, Jeong B, Yoo SH, Olson DP, Doyle FJ, Takahashi JS.
      The suprachiasmatic nucleus (SCN) acts as a master pacemaker driving circadian behavior and physiology. Although the SCN is small, it is composed of many cell types, making it difficult to study the roles of particular cells. Here we develop bioluminescent circadian reporter mice that are Cre dependent, allowing the circadian properties of genetically defined populations of cells to be studied in real time. Using a Color-Switch PER2::LUCIFERASE reporter that switches from red PER2::LUCIFERASE to green PER2::LUCIFERASE upon Cre recombination, we assess circadian rhythms in two of the major classes of peptidergic neurons in the SCN: AVP (arginine vasopressin) and VIP (vasoactive intestinal polypeptide). Surprisingly, we find that circadian function in AVP neurons, not VIP neurons, is essential for autonomous network synchrony of the SCN and stability of circadian rhythmicity.
    Keywords:  Per2 gene; SCN; bioluminescence imaging; circadian rhythms; luciferase; neuronal coupling; neuronal network; suprachiasmatic nucleus
  2. Curr Opin Cell Biol. 2020 Aug 06. pii: S0955-0674(20)30095-8. [Epub ahead of print]67 17-26
    Chakrabarti S, Michor F.
      Oscillations of the cellular circadian clock have emerged as an important regulator of many physiological processes, both in health and in disease. One such process, cellular proliferation, is being increasingly recognized to be affected by the circadian clock. Here, we review how a combination of experimental and theoretical work has furthered our understanding of the way circadian clocks couple to the cell cycle and play a role in tissue homeostasis and cancer. Finally, we discuss recently introduced methods for modeling coupling of clocks based on techniques from survival analysis and machine learning and highlight their potential importance for future studies.
    Keywords:  Circadian clock; Computational biology; Mathematical modeling