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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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Organization of the Circadian Oscillator Networks(A) Random coupling (type 1). The probability that two oscillators are connected is independent of their positions.(B) Nearest-neighbor coupling (type 2). Oscillators are on a grid with a Euclidian distance d. Circle representing oscillators are color-coded for their distance from the central black oscillator. Black, red, orange, blue, gray, and white circles are at distances d = 0, 1,, 2,, and 2, respectively. Two oscillators are connected if their distance is less than a threshold dmax.(C) SCN-like coupling (type 3). The SCN is divided in four regions, left and right VL regions (dark blue and red, respectively), and left and right DM regions (light blue and red, respectively; the green part is the intersection between left and right DM regions). Each dot represents an oscillator. Projections from the VL regions to their respective DM regions are indicated by light gray arcs. Projections from one cell to another are assigned randomly, with probability 0.5 for a DM cell to receive a projection.(D) Representation of a 3-D SCN. Each dot is a cell, and the color gradient indicates the VL–DM axis (dark cells are on the VL side and light cells are on the DM side, corresponding to the vertical axis in [C]). For type 3 coupling in a 3-D SCN, the regions are defined in the same way as in 2-D (C).
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pcbi-0030068-g002: Organization of the Circadian Oscillator Networks(A) Random coupling (type 1). The probability that two oscillators are connected is independent of their positions.(B) Nearest-neighbor coupling (type 2). Oscillators are on a grid with a Euclidian distance d. Circle representing oscillators are color-coded for their distance from the central black oscillator. Black, red, orange, blue, gray, and white circles are at distances d = 0, 1,, 2,, and 2, respectively. Two oscillators are connected if their distance is less than a threshold dmax.(C) SCN-like coupling (type 3). The SCN is divided in four regions, left and right VL regions (dark blue and red, respectively), and left and right DM regions (light blue and red, respectively; the green part is the intersection between left and right DM regions). Each dot represents an oscillator. Projections from the VL regions to their respective DM regions are indicated by light gray arcs. Projections from one cell to another are assigned randomly, with probability 0.5 for a DM cell to receive a projection.(D) Representation of a 3-D SCN. Each dot is a cell, and the color gradient indicates the VL–DM axis (dark cells are on the VL side and light cells are on the DM side, corresponding to the vertical axis in [C]). For type 3 coupling in a 3-D SCN, the regions are defined in the same way as in 2-D (C).

Mentions: To simulate synchronization within the SCN, we constructed a network of coupled but damped molecular circadian oscillators. The model is built in two levels. First, on a single-cell level, we used a detailed molecular model to describe (1) the intracellular dynamics of clock genes and proteins, (2) the circadian neurotransmitter release by clock proteins, and (3) a simplified two-step signaling cascade leading to gene activation in response to neurotransmitter release (Figure 1). Second, on the “tissue” level, we placed the cells on a grid with the topology of a 2-D or 3-D SCN, and coupled them. We considered several coupling schemes mimicking different experimental conditions: (1) random sparse coupling (type 1, Figure 2A), (2) nearest-neighbor coupling (type 2, Figure 2B), and (3) SCN-like coupling combining nearest-neighbor and sparse coupling (type 3, Figure 2C).


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

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

Organization of the Circadian Oscillator Networks(A) Random coupling (type 1). The probability that two oscillators are connected is independent of their positions.(B) Nearest-neighbor coupling (type 2). Oscillators are on a grid with a Euclidian distance d. Circle representing oscillators are color-coded for their distance from the central black oscillator. Black, red, orange, blue, gray, and white circles are at distances d = 0, 1,, 2,, and 2, respectively. Two oscillators are connected if their distance is less than a threshold dmax.(C) SCN-like coupling (type 3). The SCN is divided in four regions, left and right VL regions (dark blue and red, respectively), and left and right DM regions (light blue and red, respectively; the green part is the intersection between left and right DM regions). Each dot represents an oscillator. Projections from the VL regions to their respective DM regions are indicated by light gray arcs. Projections from one cell to another are assigned randomly, with probability 0.5 for a DM cell to receive a projection.(D) Representation of a 3-D SCN. Each dot is a cell, and the color gradient indicates the VL–DM axis (dark cells are on the VL side and light cells are on the DM side, corresponding to the vertical axis in [C]). For type 3 coupling in a 3-D SCN, the regions are defined in the same way as in 2-D (C).
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getmorefigures.php?uid=PMC1851983&req=5

pcbi-0030068-g002: Organization of the Circadian Oscillator Networks(A) Random coupling (type 1). The probability that two oscillators are connected is independent of their positions.(B) Nearest-neighbor coupling (type 2). Oscillators are on a grid with a Euclidian distance d. Circle representing oscillators are color-coded for their distance from the central black oscillator. Black, red, orange, blue, gray, and white circles are at distances d = 0, 1,, 2,, and 2, respectively. Two oscillators are connected if their distance is less than a threshold dmax.(C) SCN-like coupling (type 3). The SCN is divided in four regions, left and right VL regions (dark blue and red, respectively), and left and right DM regions (light blue and red, respectively; the green part is the intersection between left and right DM regions). Each dot represents an oscillator. Projections from the VL regions to their respective DM regions are indicated by light gray arcs. Projections from one cell to another are assigned randomly, with probability 0.5 for a DM cell to receive a projection.(D) Representation of a 3-D SCN. Each dot is a cell, and the color gradient indicates the VL–DM axis (dark cells are on the VL side and light cells are on the DM side, corresponding to the vertical axis in [C]). For type 3 coupling in a 3-D SCN, the regions are defined in the same way as in 2-D (C).
Mentions: To simulate synchronization within the SCN, we constructed a network of coupled but damped molecular circadian oscillators. The model is built in two levels. First, on a single-cell level, we used a detailed molecular model to describe (1) the intracellular dynamics of clock genes and proteins, (2) the circadian neurotransmitter release by clock proteins, and (3) a simplified two-step signaling cascade leading to gene activation in response to neurotransmitter release (Figure 1). Second, on the “tissue” level, we placed the cells on a grid with the topology of a 2-D or 3-D SCN, and coupled them. We considered several coupling schemes mimicking different experimental conditions: (1) random sparse coupling (type 1, Figure 2A), (2) nearest-neighbor coupling (type 2, Figure 2B), and (3) SCN-like coupling combining nearest-neighbor and sparse coupling (type 3, Figure 2C).

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