For animals living in temperate latitudes, seasonal changes in day length are an important cue for adaptations of their physiology and behavior to the altered environmental conditions. The suprachiasmatic nucleus (SCN) is known as the central circadian clock in mammals, but may also play an important role in adaptations to different photoperiods. The SCN receives direct light input from the retina and is able to encode day-length by approximating the waveform of the electrical activity rhythm to the duration of daylight. Changing the overall waveform requires a reorganization of the neuronal network within the SCN with a change in the degree of synchrony between the neurons; however, the underlying mechanisms are yet unknown. In the present study we used PER2::LUC bioluminescence imaging in cultured SCN slices to characterize network dynamics on the single-cell level and we aimed to provide evidence for a role of modulations in coupling strength in the photoperiodic-induced phase dispersal. Exposure to long photoperiod (LP) induced a larger distribution of peak times of the single-cell PER2::LUC rhythms in the anterior SCN, compared to short photoperiod. Interestingly, the cycle-to-cycle variability in single-cell period of PER2::LUC rhythms is also higher in the anterior SCN in LP, and is positively correlated with peak time dispersal. Applying a new, impartial community detection method on the time series data of the PER2::LUC rhythm revealed two clusters of cells with a specific spatial distribution, which we define as dorsolateral and ventromedial SCN. Post hoc analysis of rhythm characteristics of these clusters showed larger cycle-to-cycle single-cell period variability in the dorsolateral compared to the ventromedial cluster in the anterior SCN. We conclude that a change in coupling strength within the SCN network is a plausible explanation to the observed changes in single-cell period variability, which can contribute to the photoperiod-induced phase distribution.

Adult neurogenesis generates functional neurons from neural stem cells present in specific brain regions. It is largely confined to two main regions: the subventricular zone of the lateral ventricle, and the subgranular zone of the dentate gyrus (DG), in the hippocampus. With age, the function of the hippocampus and particularly the DG is impaired. For instance, adult neurogenesis is decreased with aging, in both proliferating and differentiation of newborn cells, while in parallel an age-associated decline in cognitive performance is often seen. Surprisingly, the synaptogenic potential of adult-born neurons is only marginally influenced by aging. Therefore, although proliferation, differentiation, and synaptogenesis of adult-born new neurons in the DG are closely related to each other, they are differentially affected by aging. In this review we discuss the crucial roles of a novel class of recently discovered modulators of gene expression, the small non-coding RNAs, in the regulation of adult neurogenesis. Multiple small non-coding RNAs are differentially expressed in the hippocampus. In particular a subgroup of the small non-coding RNAs, the microRNAs, fine-tune the progression of adult neurogenesis. This makes small non-coding RNAs appealing candidates to orchestrate the functional alterations in adult neurogenesis and cognition associated with aging. Finally, we summarize observations that link changes in circulating levels of steroid hormones with alterations in adult neurogenesis, cognitive decline, and vulnerability to psychopathology in advanced age, and discuss a potential interplay between steroid hormone receptors and microRNAs in cognitive decline in aging individuals.

Aging impairs circadian clock function, leading to disrupted sleep-wake patterns and a reduced capability to adapt to changes in environmental light conditions. This makes shift work or the changing of time zones challenging for the elderly and, importantly, is associated with the development of age-related diseases. However, it is unclear what levels of the clock machinery are affected by aging, which is relevant for the development of targeted interventions. We found that naturally aged mice of >24 months had a reduced rhythm amplitude in behavior compared with young controls (3-6 months). Moreover, the old animals had a strongly reduced ability to adapt to short photoperiods. Recording PER2::LUC protein expression in the suprachiasmatic nucleus revealed no impairment of the rhythms in PER2 protein under the 3 different photoperiods tested (LD: 8:16, 12:12, and 16:8). Thus, we observed a discrepancy between the behavioral phenotype and the molecular clock, and we conclude that the aging-related deficits emerge downstream of the core molecular clock. Since it is known that aging affects several intracellular and membrane components of the central clock cells, it is likely that an impairment of the interaction between the molecular clock and these components is contributing to the deficits in photoperiod adaptation.

Neural systems are organized in a modular way, serving multiple functionalities. This multiplicity requires that both positive (e.g. excitatory, phase-coherent) and negative (e.g. inhibitory, phase-opposing) interactions take place across brain modules. Unfortunately, most methods to detect modules from time series either neglect or convert to positive, any measured negative correlation. This may leave a significant part of the sign-dependent functional structure undetected. Here we present a novel method, based on random matrix theory, for the identification of sign-dependent modules in the brain. Our method filters out both local (unit-specific) noise and global (system-wide) dependencies that typically obfuscate the presence of such structure. The method is guaranteed to identify an optimally contrasted functional ‘signature’, i.e. a partition into modules that are positively correlated internally and negatively correlated across. The method is purely data-driven, does not use any arbitrary threshold or network projection, and outputs only statistically significant structure. In measurements of neuronal gene expression in the biological clock of mice, the method systematically uncovers two otherwise undetectable, negatively correlated modules whose relative size and mutual interaction strength are found to depend on photoperiod.

Lipid metabolism is under the control of the circadian system and circadian dysregulation has been linked to obesity and dyslipidemia. These factors and outcomes have also been associated to, or affected by, the process of aging. Here, we investigated whether murine white (WAT) and brown (BAT) adipose tissue lipids exhibit rhythmicity and if this is affected by aging. To this end, we have measured the 24 h lipid profiles of WAT and BAT using a global lipidomics analysis of > 1100 lipids. We observed rhythmicity in nearly all lipid classes including glycerolipids, glycerophospholipids, sterol lipids and sphingolipids. Overall, ~ 22% of the analyzed lipids were considered rhythmic in WAT and BAT. Despite a general accumulation of lipids upon aging the fraction of oscillating lipids decreased in both tissues to 14% and 18%, respectively. Diurnal profiles of lipids in BAT appeared to depend on the lipid acyl chain length and this specific regulation was lost in aged mice. Our study revealed how aging affects the rhythmicity of lipid metabolism and could contribute to the quest for targets that improve diurnal lipid homeostasis to maintain cardiometabolic health during aging.