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Synchronization-induced rhythmicity of circadian oscillators in the suprachiasmatic nucleus.

Bernard S, Gonze D, Cajavec B, Herzel H, Kramer A - PLoS Comput. Biol. (2007)

Bottom Line: The authors simulated different experimental conditions and found that: (1) in normal, constant conditions, coupled circadian oscillators quickly synchronize and produce a coherent output; (2) in large populations, such oscillators either synchronize or gradually lose rhythmicity, but do not run out of phase, demonstrating that rhythmicity and synchrony are codependent; (3) the number of oscillators and connectivity are important for these synchronization properties; (4) slow oscillators have a higher impact on the period in mixed populations; and (5) coupled circadian oscillators can be efficiently entrained by light-dark cycles.Based on these results, it is predicted that: (1) a majority of SCN neurons needs periodic synchronization signal to be rhythmic; (2) a small number of neurons or a low connectivity results in desynchrony; and (3) amplitudes and phases of neurons are negatively correlated.The authors conclude that to understand the orchestration of timekeeping in the SCN, intracellular circadian clocks cannot be isolated from their intercellular communication components.

View Article: PubMed Central - PubMed

Affiliation: Institute of Applied and Computational Mathematics, Foundation for Research and Technology-Hellas, Heraklion, Crete, Greece. samubernard@gmail.com

ABSTRACT
The suprachiasmatic nuclei (SCN) host a robust, self-sustained circadian pacemaker that coordinates physiological rhythms with the daily changes in the environment. Neuronal clocks within the SCN form a heterogeneous network that must synchronize to maintain timekeeping activity. Coherent circadian output of the SCN tissue is established by intercellular signaling factors, such as vasointestinal polypeptide. It was recently shown that besides coordinating cells, the synchronization factors play a crucial role in the sustenance of intrinsic cellular rhythmicity. Disruption of intercellular signaling abolishes sustained rhythmicity in a majority of neurons and desynchronizes the remaining rhythmic neurons. Based on these observations, the authors propose a model for the synchronization of circadian oscillators that combines intracellular and intercellular dynamics at the single-cell level. The model is a heterogeneous network of circadian neuronal oscillators where individual oscillators are damped rather than self-sustained. The authors simulated different experimental conditions and found that: (1) in normal, constant conditions, coupled circadian oscillators quickly synchronize and produce a coherent output; (2) in large populations, such oscillators either synchronize or gradually lose rhythmicity, but do not run out of phase, demonstrating that rhythmicity and synchrony are codependent; (3) the number of oscillators and connectivity are important for these synchronization properties; (4) slow oscillators have a higher impact on the period in mixed populations; and (5) coupled circadian oscillators can be efficiently entrained by light-dark cycles. Based on these results, it is predicted that: (1) a majority of SCN neurons needs periodic synchronization signal to be rhythmic; (2) a small number of neurons or a low connectivity results in desynchrony; and (3) amplitudes and phases of neurons are negatively correlated. The authors conclude that to understand the orchestration of timekeeping in the SCN, intracellular circadian clocks cannot be isolated from their intercellular communication components.

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Simulation of Entrainment of a 2-D SCN Slice by a 12:12 LD Cycle(A) Simulation of the evolution of Per/Cry mRNA over 48 h of 309 coupled cells (VL, n = 102; DM, n = 207) in a 2-D SCN slice with a type 3 coupling (dmax = 3.5, 50% of neuronal projections, 4% average period gradient, K = 1.0, L0 = 0.22). The black bars indicate a dark phase (color code as in Figure 3A). Individual oscillators have an average period of 23.7 ± 1.2 h. Initial conditions were chosen randomly. The first 72 h of transient were discarded, and the time from 72 h to 144 h was retained.(B,C) Raster plot of Per/Cry mRNA activity in oscillators, organized according to their regions (from bottom up: VLL, left VL region; VLR, right VL region; DML, left DM region; DMR, right DM region; and Int, intersection between left and right DM regions). The concentration of Per/Cry mRNA for each oscillator is represented by colors (blue, low concentration; red, high concentration).(B) 12:12 LD cycle.(C) 12:12 LD cycle with a 12 h phase shift at t = 84 h.
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pcbi-0030068-g007: Simulation of Entrainment of a 2-D SCN Slice by a 12:12 LD Cycle(A) Simulation of the evolution of Per/Cry mRNA over 48 h of 309 coupled cells (VL, n = 102; DM, n = 207) in a 2-D SCN slice with a type 3 coupling (dmax = 3.5, 50% of neuronal projections, 4% average period gradient, K = 1.0, L0 = 0.22). The black bars indicate a dark phase (color code as in Figure 3A). Individual oscillators have an average period of 23.7 ± 1.2 h. Initial conditions were chosen randomly. The first 72 h of transient were discarded, and the time from 72 h to 144 h was retained.(B,C) Raster plot of Per/Cry mRNA activity in oscillators, organized according to their regions (from bottom up: VLL, left VL region; VLR, right VL region; DML, left DM region; DMR, right DM region; and Int, intersection between left and right DM regions). The concentration of Per/Cry mRNA for each oscillator is represented by colors (blue, low concentration; red, high concentration).(B) 12:12 LD cycle.(C) 12:12 LD cycle with a 12 h phase shift at t = 84 h.

Mentions: To test whether our model is able to entrain to LD cycles and to analyze entrainment dynamics, we simulated a 12 h–12 h LD cycle in a 2-D SCN with a type 3 coupling by imposing a periodic forcing on the expression of Per/Cry gene in the VL cells. Through neuronal projections, VL cells entrained the DM cells (Figure 7A and 7B, and Video S3). Starting from completely desynchronized cells, high synchrony (R = 0.92) and phase-locking to the LD cycle (with a 24-h period) are reached very fast, within 72 h. The phases of DM cells were slightly more advanced than those of the light-inducible VL cells (unpublished data), as observed experimentally [20]. After a 12-h phase-shift in the LD cycle, VL cells resumed their phase quickly (after 2 d), while DM cells took more than 10 d to resynchronize to the LD cycle (Figure 7C). These results are in agreement with experimental findings [32], and show that entrainment by a LD cycle is efficient even if only a fraction of the cells can respond to the light signal (102 out of 309), but also that the light-insensitive cells take a longer time to adjust their phase.


Synchronization-induced rhythmicity of circadian oscillators in the suprachiasmatic nucleus.

Bernard S, Gonze D, Cajavec B, Herzel H, Kramer A - PLoS Comput. Biol. (2007)

Simulation of Entrainment of a 2-D SCN Slice by a 12:12 LD Cycle(A) Simulation of the evolution of Per/Cry mRNA over 48 h of 309 coupled cells (VL, n = 102; DM, n = 207) in a 2-D SCN slice with a type 3 coupling (dmax = 3.5, 50% of neuronal projections, 4% average period gradient, K = 1.0, L0 = 0.22). The black bars indicate a dark phase (color code as in Figure 3A). Individual oscillators have an average period of 23.7 ± 1.2 h. Initial conditions were chosen randomly. The first 72 h of transient were discarded, and the time from 72 h to 144 h was retained.(B,C) Raster plot of Per/Cry mRNA activity in oscillators, organized according to their regions (from bottom up: VLL, left VL region; VLR, right VL region; DML, left DM region; DMR, right DM region; and Int, intersection between left and right DM regions). The concentration of Per/Cry mRNA for each oscillator is represented by colors (blue, low concentration; red, high concentration).(B) 12:12 LD cycle.(C) 12:12 LD cycle with a 12 h phase shift at t = 84 h.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1851983&req=5

pcbi-0030068-g007: Simulation of Entrainment of a 2-D SCN Slice by a 12:12 LD Cycle(A) Simulation of the evolution of Per/Cry mRNA over 48 h of 309 coupled cells (VL, n = 102; DM, n = 207) in a 2-D SCN slice with a type 3 coupling (dmax = 3.5, 50% of neuronal projections, 4% average period gradient, K = 1.0, L0 = 0.22). The black bars indicate a dark phase (color code as in Figure 3A). Individual oscillators have an average period of 23.7 ± 1.2 h. Initial conditions were chosen randomly. The first 72 h of transient were discarded, and the time from 72 h to 144 h was retained.(B,C) Raster plot of Per/Cry mRNA activity in oscillators, organized according to their regions (from bottom up: VLL, left VL region; VLR, right VL region; DML, left DM region; DMR, right DM region; and Int, intersection between left and right DM regions). The concentration of Per/Cry mRNA for each oscillator is represented by colors (blue, low concentration; red, high concentration).(B) 12:12 LD cycle.(C) 12:12 LD cycle with a 12 h phase shift at t = 84 h.
Mentions: To test whether our model is able to entrain to LD cycles and to analyze entrainment dynamics, we simulated a 12 h–12 h LD cycle in a 2-D SCN with a type 3 coupling by imposing a periodic forcing on the expression of Per/Cry gene in the VL cells. Through neuronal projections, VL cells entrained the DM cells (Figure 7A and 7B, and Video S3). Starting from completely desynchronized cells, high synchrony (R = 0.92) and phase-locking to the LD cycle (with a 24-h period) are reached very fast, within 72 h. The phases of DM cells were slightly more advanced than those of the light-inducible VL cells (unpublished data), as observed experimentally [20]. After a 12-h phase-shift in the LD cycle, VL cells resumed their phase quickly (after 2 d), while DM cells took more than 10 d to resynchronize to the LD cycle (Figure 7C). These results are in agreement with experimental findings [32], and show that entrainment by a LD cycle is efficient even if only a fraction of the cells can respond to the light signal (102 out of 309), but also that the light-insensitive cells take a longer time to adjust their phase.

Bottom Line: The authors simulated different experimental conditions and found that: (1) in normal, constant conditions, coupled circadian oscillators quickly synchronize and produce a coherent output; (2) in large populations, such oscillators either synchronize or gradually lose rhythmicity, but do not run out of phase, demonstrating that rhythmicity and synchrony are codependent; (3) the number of oscillators and connectivity are important for these synchronization properties; (4) slow oscillators have a higher impact on the period in mixed populations; and (5) coupled circadian oscillators can be efficiently entrained by light-dark cycles.Based on these results, it is predicted that: (1) a majority of SCN neurons needs periodic synchronization signal to be rhythmic; (2) a small number of neurons or a low connectivity results in desynchrony; and (3) amplitudes and phases of neurons are negatively correlated.The authors conclude that to understand the orchestration of timekeeping in the SCN, intracellular circadian clocks cannot be isolated from their intercellular communication components.

View Article: PubMed Central - PubMed

Affiliation: Institute of Applied and Computational Mathematics, Foundation for Research and Technology-Hellas, Heraklion, Crete, Greece. samubernard@gmail.com

ABSTRACT
The suprachiasmatic nuclei (SCN) host a robust, self-sustained circadian pacemaker that coordinates physiological rhythms with the daily changes in the environment. Neuronal clocks within the SCN form a heterogeneous network that must synchronize to maintain timekeeping activity. Coherent circadian output of the SCN tissue is established by intercellular signaling factors, such as vasointestinal polypeptide. It was recently shown that besides coordinating cells, the synchronization factors play a crucial role in the sustenance of intrinsic cellular rhythmicity. Disruption of intercellular signaling abolishes sustained rhythmicity in a majority of neurons and desynchronizes the remaining rhythmic neurons. Based on these observations, the authors propose a model for the synchronization of circadian oscillators that combines intracellular and intercellular dynamics at the single-cell level. The model is a heterogeneous network of circadian neuronal oscillators where individual oscillators are damped rather than self-sustained. The authors simulated different experimental conditions and found that: (1) in normal, constant conditions, coupled circadian oscillators quickly synchronize and produce a coherent output; (2) in large populations, such oscillators either synchronize or gradually lose rhythmicity, but do not run out of phase, demonstrating that rhythmicity and synchrony are codependent; (3) the number of oscillators and connectivity are important for these synchronization properties; (4) slow oscillators have a higher impact on the period in mixed populations; and (5) coupled circadian oscillators can be efficiently entrained by light-dark cycles. Based on these results, it is predicted that: (1) a majority of SCN neurons needs periodic synchronization signal to be rhythmic; (2) a small number of neurons or a low connectivity results in desynchrony; and (3) amplitudes and phases of neurons are negatively correlated. The authors conclude that to understand the orchestration of timekeeping in the SCN, intracellular circadian clocks cannot be isolated from their intercellular communication components.

Show MeSH
Related in: MedlinePlus