Output from VIP cells of the mammalian central clock regulates daily physiological rhythms

The suprachiasmatic nucleus (SCN) circadian clock is critical for optimising daily cycles in mammalian physiology and behaviour. The roles of the various SCN cell types in communicating timing information to downstream physiological systems remain incompletely understood, however. In particular, while vasoactive intestinal polypeptide (VIP) signalling is essential for SCN function and whole animal circadian rhythmicity, the specific contributions of VIP cell output to physiological control remains uncertain. Here we reveal a key role for SCN VIP cells in central clock output. Using multielectrode recording and optogenetic manipulations, we show that VIP neurons provide coordinated daily waves of GABAergic input to target cells across the paraventricular hypothalamus and ventral thalamus, supressing their activity during the mid to late day. Using chemogenetic manipulation, we further demonstrate specific roles for this circuitry in the daily control of heart rate and corticosterone secretion, collectively establishing SCN VIP cells as influential regulators of physiological timing

Phase Shifting Capacity of the Circadian Pacemaker Determined by the SCN Neuronal Network Organization

In mammals, a major circadian pacemaker that drives daily rhythms is located in the suprachiasmatic nuclei (SCN), at the base of the hypothalamus. The SCN receive direct light input via the retino-hypothalamic tract. Light during the early night induces phase delays of circadian rhythms while during the late night it leads to phase advances. The effects of light on the circadian system are strongly dependent on the photoperiod to which animals are exposed. An explanation for this phenomenon is currently lacking.We recorded running wheel activity in C57 mice and observed large amplitude phase shifts in short photoperiods and small shifts in long photoperiods. We investigated whether these different light responses under short and long days are expressed within the SCN by electrophysiological recordings of electrical impulse frequency in SCN slices. Application of N-methyl-D-aspartate (NMDA) induced sustained increments in electrical activity that were not significantly different in the slices from long and short photoperiods. These responses led to large phase shifts in slices from short days and small phase shifts in slices from long days. An analysis of neuronal subpopulation activity revealed that in short days the amplitude of the rhythm was larger than in long days.The data indicate that the photoperiodic dependent phase responses are intrinsic to the SCN. In contrast to earlier predictions from limit cycle theory, we observed large phase shifting responses in high amplitude rhythms in slices from short days, and small shifts in low amplitude rhythms in slices from long days. We conclude that the photoperiodic dependent phase responses are determined by the SCN and propose that synchronization among SCN neurons enhances the phase shifting capacity of the circadian system

Voluntary exercise can strengthen the circadian system in aged mice

Consistent daily rhythms are important to healthy aging according to studies linking disrupted circadian rhythms with negative health impacts. We studied the effects of age and exercise on baseline circadian rhythms and on the circadian system's ability to respond to the perturbation induced by an 8 h advance of the light:dark (LD) cycle as a test of the system's robustness. Mice (male, mPer2luc/C57BL/6) were studied at one of two ages: 3.5 months (n = 39) and >18 months (n = 72). We examined activity records of these mice under entrained and shifted conditions as well as mPER2::LUC measures ex vivo to assess circadian function in the suprachiasmatic nuclei (SCN) and important target organs. Age was associated with reduced running wheel use, fragmentation of activity, and slowed resetting in both behavioral and molecular measures. Furthermore, we observed that for aged mice, the presence of a running wheel altered the amplitude of the spontaneous firing rate rhythm in the SCN in vitro. Following a shift of the LD cycle, both young and aged mice showed a change in rhythmicity properties of the mPER2::LUC oscillation of the SCN in vitro, and aged mice exhibited longer lasting internal desynchrony. Access to a running wheel alleviated some age-related changes in the circadian system. In an additional experiment, we replicated the effect of the running wheel, comparing behavioral and in vitro results from aged mice housed with or without a running wheel (>21 months, n = 8 per group, all examined 4 days after the shift). The impact of voluntary exercise on circadian rhythm properties in an aged animal is a novel finding and has implications for the health of older people living with environmentally induced circadian disruption

Effect of Network Architecture on Synchronization and Entrainment Properties of the Circadian Oscillations in the Suprachiasmatic Nucleus

In mammals, the suprachiasmatic nucleus (SCN) of the hypothalamus constitutes the central circadian pacemaker. The SCN receives light signals from the retina and controls peripheral circadian clocks (located in the cortex, the pineal gland, the liver, the kidney, the heart, etc.). This hierarchical organization of the circadian system ensures the proper timing of physiological processes. In each SCN neuron, interconnected transcriptional and translational feedback loops enable the circadian expression of the clock genes. Although all the neurons have the same genotype, the oscillations of individual cells are highly heterogeneous in dispersed cell culture: many cells present damped oscillations and the period of the oscillations varies from cell to cell. In addition, the neurotransmitters that ensure the intercellular coupling, and thereby the synchronization of the cellular rhythms, differ between the two main regions of the SCN. In this work, a mathematical model that accounts for this heterogeneous organization of the SCN is presented and used to study the implication of the SCN network topology on synchronization and entrainment properties. The results show that oscillations with larger amplitude can be obtained with scale-free networks, in contrast to random and local connections. Networks with the small-world property such as the scale-free networks used in this work can adapt faster to a delay or advance in the light/dark cycle (jet lag). Interestingly a certain level of cellular heterogeneity is not detrimental to synchronization performances, but on the contrary helps resynchronization after jet lag. When coupling two networks with different topologies that mimic the two regions of the SCN, efficient filtering of pulse-like perturbations in the entrainment pattern is observed. These results suggest that the complex and heterogeneous architecture of the SCN decreases the sensitivity of the network to short entrainment perturbations while, at the same time, improving its adaptation abilities to long term changes

Phase resetting of the mammalian circadian clock relies on a rapid shift of a small population of pacemaker neurons.

The circadian pacemaker of the suprachiasmatic nuclei (SCN) contains a major pacemaker for 24 h rhythms that is synchronized to the external light-dark cycle. In response to a shift in the external cycle, neurons of the SCN resynchronize with different pace. We performed electrical activity recordings of the SCN of rats in vitro following a 6 hour delay of the light-dark cycle and observed a bimodal electrical activity pattern with a shifted and an unshifted component. The shifted component was relatively narrow as compared to the unshifted component (2.2 h and 5.7 h, respectively). Curve fitting and simulations predicted that less than 30% of the neurons contribute to the shifted component and that their phase distribution is small. This prediction was confirmed by electrophysiological recordings of neuronal subpopulations. Only 25% of the neurons exhibited an immediate shift in the phase of the electrical activity rhythms, and the phases of the shifted subpopulations appeared significantly more synchronized as compared to the phases of the unshifted subpopulations (p<0.05). We also performed electrical activity recordings of the SCN following a 9 hour advance of the light-dark cycle. The phase advances induced a large desynchrony among the neurons, but consistent with the delays, only 19% of the neurons peaked at the mid of the new light phase. The data suggest that resetting of the central circadian pacemaker to both delays and advances is brought about by an initial shift of a relatively small group of neurons that becomes highly synchronized following a shift in the external cycle. The high degree of synchronization of the shifted neurons may add to the ability of this group to reset the pacemaker. The large desynchronization observed following advances may contribute to the relative difficulty of the circadian system to respond to advanced light cycles

Simulations of electrical activity patterns with two components.

<p>The black line shows the resulting multiunit pattern of two components with peak activity at ZT 9 (red dotted line) and ZT 13 (blue dotted line). The neurons of each component show a Gaussian distribution with certain distribution-width (σ). (A) Both populations have the same number of neurons and the same distribution. This leads to a single peak in the multiunit activity pattern. (B) The number of neurons in the shifted component is decreased, resulting in a unimodal multiunit pattern. (C) The number of neurons in the shifted component is decreased and the distribution of the shifted component is narrower, which leads to a bimodal multiunit pattern. (D) If the number of neurons is slightly increased with respect to (C), and the distribution of the shifted component is still narrow, the second peak becomes rapidly higher, see also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0025437#pone-0025437-g001" target="_blank">figure 1</a> C. (E) Search-space that shows the effect of the number of neurons in each component and of their relative distribution to the multiunit pattern. The multiunit pattern becomes bimodal when the number of neurons of the shifted component is relatively small as compared to the total number of neurons (x-axis) and when the degree of synchronization of the shifted component is high (y-axis). The examples shown in (A)-(D) are depicted by the dots in the search-space.</p

Relative number of action potentials contributing to each component.

<p>(A) The total area under each of the components was used to determine the relative number of action potentials contributing to each component. (B) Gaussian functions fitted to the smoothed multiunit activity pattern. The black line is the smoothed multiunit activity pattern. The blue line is the total fitted pattern, and the Gaussian functions are shown below the fitted signal. (C) The area of the unshifted component as determined in (A) was 74% of the total area, while the area of the shifted component was 26%. (D) The relative area of the unshifted component, as determined in (B), was 79%, and of the shifted component was 21%.</p

Subpopulation analysis of the electrical activity profile after the shift in LD.

<p>(A and B) Two examples of the subpopulations (left ordinate axis) and multiunit activity pattern (right ordinate axis) for the same recording. The peak times of the subpopulations, indicated by the dots, were determined relative to the trough of the multiunit pattern (indicated by the red vertical line). (C) The number of subpopulations found in the unshifted component was higher than that in the shifted component, and showed a broader distribution.</p

Width and time of peak activity for both components.

<p>(A) Raw multiunit activity data following a shift of the light-dark cycle. After smoothing of the data, the trough between both components was determined as well as the peak times. The width of the unshifted and the shifted component was determined by drawing a horizontal line from the trough to the opposing slope of the component's peak. The ZT refers to the shifted Zeitgeber time. (B) The peak time for the unshifted and shifted component was at ZT 2.7±0.4 h, and at ZT 6.6±0.4 h respectively. The difference in peak time was significant (p<0.01). (C) The width of the peak of the unshifted and shifted component was 5.7±0.4 h and 2.2±0.3 h, respectively, which was significantly different (p<0.01).</p