Features of age-related response to sleep deprivation: in vivo experimental studies

Age-related changes in the eating behavior of mice under sleep deprivation influence

Disturbances in melatonin metabolism that occur with insomnia are associated with altered eating behavior and increased food intake [50–52]. Therefore, we first compared eating behavior characteristics in mice with a regular sleep-awake cycle and sleep deprivation. The study revealed that each animal from the “Intact” and “Control” groups consumed on average 8.8±3 ml of water and 5-7 g of food per day. The total time of sleep was 10 hours a day, dividing into approximate periods of 1 hour. Despite the fact that mice are nocturnal burrowing animals and usually have a main wakefulness period at night, the sleep period did not exceed 3 hours.

Sleep deprivation modelling led to an increase in food intake by mice. Consumption of water and food in the “SD” group increased by 1.5-2 times, although the mice spent only 13 hours a day in the home cage and slept most of that time. Interestingly, the severity of the observed changes depended on the mice age. From the end of the 5th session of sleep deprivation, the adult mice (7-9 months) began to consume large quantities of food and water and quickly fell asleep in their home cages. Their activity decreased significantly, and the mice ceased to resist when we removed them from the platform. The response to nighttime signals was minimal by the end of sleep deprivation modelling. The young mice began to demonstrate the decreased activity from day 7 after the beginning of sleep deprivation, although they increased the consumption of food and water from the second day of the modeled stress.

Weight characteristics of mice were changed in an age-dependent manner (Figure 2). Initially, the adult mice weighed more than the young ones (Supplementary Figure 1); however, both young and adult animals from the “Intact” and “Control” groups had no significant changes in the body weight characteristics between the beginning and the end of the experiment. In contrast, sleep deprivation leads to significant weight loss in young mice after the end of the modeled stress despite their active food and water consumption. On the other hand, the adult mice gained weight. Significant weight changes were observed in the “SD adult” group relative to the “Intact” values.

Features of locomotor and orienting-exploratory activity of mice after sleep deprivation

Analysis of animals’ behavior in the “Open Field” test showed a significant increase in locomotor activity of mice exposed to sleep deprivation modelling (Table 1). This effect was observed in both young and adult mice. The average speed crossing the arena squares in the “SD young” and “SD adult” groups was 0.45 ± 0.02 squares/s and 0.39 ± 0.02 squares/s respectively that significantly exceeded the intact and control values.

Moreover, the mice subjected to sleep deprivation gained increased exploratory activity. The mice of both aging groups left from the arena center and actively moved along its periphery. Of note, the young mice were more agile. The number of crossed squares in the arena periphery in the “SD young” and “SD adult” groups was 109.4±7.36 and 86.85±4.67, respectively. The young mice also had a more pronounced hole board exploratory behavior (number of peeks in holes: “SD young” 42.1±4.08, “SD adult” 32.04±1.85, p≤0.05). At the same time, the vertical motor activity was increased in adult mice compared to the young ones (the number of upright postures: “SD young” 4.3±1.0, “SD adult” 10.2±1.3, p≤0.05, Supplementary Table 1). An active search for an exit out of the arena points to an unstable emotional state and the increased anxiety level in mice. It can be assumed that such behavioral changes are associated with gradually cumulative response to long-term sleep deprivation and related to hyperactivity of the nervous system after chronic stress. Young mice respond to stress more actively, probably due to their increased adaptive capacity relative to the adult animals.

Features of spatial learning and working memory of mice during aging and sleep deprivation

Our studies have shown that aging decreases the spatial learning abilities of female mice. During the training courses in the Morris water maze, the mice of 7-9 months of age spent significantly more time searching a platform, and the number of effective attempts to achieve the platform was lower compared to the 1.5 months mice (Figure 3). The young mice demonstrated fast positive dynamics of learning and predominantly used the direct searching strategy to find the platform by the end of the training course.

Long-term memory retention was assessed by testing animals in the pool without a platform. The young and adult mice from the “Intact” group who first placed in the pool had different behavioral tactics (Figure 4). The 7-9 months mice moved around the pool chaotically and showed the greatest time of the first hit to the zone where the platform used to be located. The 1.5 months mice were more active; however, they mostly moved along the thigmotaxis zone and spent more time to reach the “platform” (Figure 4A).

The young mice who previously trained in the Morris water maze (“Control”) mainly chose active (30%) and direct (40%) searching strategies, while the strategies of adults’ specimens were evenly distributed (Figure 4A).

Sleep deprivation leads to an increase in the rates of memory traces reproduction in young mice. The animals from the “SD young” group were the first to enter the zone where the platform used to be located, and 70% of them swam straight to the target (direct searching strategy). The mice from the “SD adult” group are mostly preferred active and chaotic searching strategy (Supplementary Figure 2). Moreover, the active searching strategy was accompanied by sharp turns and reversing the direction that point to the animal's loss of concentration. The decrease in synaptic plasticity of the adult brain cortex against the background of chronic sleep deprivation influence could be assumed. Therefore, the next stage of the study aims to assess the features of morphological changes in mice's brain cortex after the modeled chronic stress.

Morphological changes in mice brain cortex under sleep deprivation influence

Histological studies revealed no significant morphological changes of the brain cortex in response to training activity in the Morris water maze. The internal granular layer of the “Intact” and “Control” groups was represented by large neurons (Figure 5). The cells in most cases were pyramidal and stellate in shape; only single rounded and oval cells were observed in the fields of view. The nuclei had a well-defined structure with a rounded and oval shape and occupied, on average, half of the cell volume. The cytoplasm had a regular structure without coarse inclusions. The vessels were not damaged. However, it is interesting to note a tendency towards contraction and branching of neuronal outgrowths in adult animals. Moreover, the average diameter of brain neurons of adult mice was decreased relative to the parameters of young mice (“Intact young” 5.5 ± 0.2 μm; “Control young” 5.3 ± 0.6 μm; “Intact adult” 4.2 ± 0.5 μm; “Control adult” 4.1 ± 0.3 μm).

Sleep deprivation modelling caused morphological changes in nerve cells. In the “SD” group, the average diameter of the soma was decreased (“SD young” 4.14 ± 0.4 μm, “SD adult” 3.9± 0.4 μm); the neurons became more elongated and less branched that point to signs of the degradation of synaptic contacts. At the same time, the appearance of new neurons was observed. This effect was more pronounced in young mice, where the number of new cells in 10 fields of view was in 2–3 times higher relative to those in adult mice (“SD young” 4.1 ± 0.94 μm, “SD adult” 0.9 ± 0.35 μm). It could be assumed that young animals have an increased adaptive potential for substantial restructuring in a sleep-awake cycle.

Mitochondrial functional activity in the mice brain under sleep deprivation influence

As a powerful stress factor, long-term sleep deprivation can trigger the cell death processes in which mitochondria are often actively involved [53, 54]. Therefore, assessment of the mitochondrial functional activity can serve as a critical parameter of brain cells adaptation to stress conditions.

Our studies revealed a tendency to decrease the main parameters of mitochondrial functional activity in young mice from the “Control” group, which is probably related to their activity in passing training courses in the Morris water maze (Table 2). Spatial learning, combined with the long-term influence of sleep deprivation, promptly adapted the mitochondrial brain cells' apparatus by activating cellular respiration through the production of molecular components in actively working mitochondria. No significant differences in the main parameters of mitochondrial functional state in mice brain of the “SD” group were found relative to the values of the “Intact” and “Control” groups.

However, it should be noted that aging potentially leads to decreasing the work of the mitochondrial respiratory chain and the intensity of oxidative phosphorylation. A downward tendency in the basal of oxygen consumption rate and mitochondrial respiration activity in inhibition of respiratory chain complex I as well as during activation of respiratory chain complex II in the adult mice from all groups were observed (Table 2). The reduced activity of respiratory chain complexes I and II could potentially serve as a trigger for decreasing the animal resistance to stressogenic effects.

Assessment of molecular markers of brain adaptation and aging processes in response to sleep deprivation influence

Next, using the RT-qPCR method, we analyzed the level of gene expression of α-subunit of hypoxia-inducible factor HIF1 (HIF1α) and perilipin 2 (PLIN2) in the mice brain after sleep deprivation modeling (Figure 6). HIF1α is one of the key participants that control oxygen homeostasis and adaptive processes in the brain under the influence of various stress-factors [55, 56]. PLIN2 is a protein involved in lipid storage and metabolism in non-adipose tissues which accumulation is regarded as a potential marker of age-related processes in the organism.

The studies revealed no significant changes in HIF1α expression level in both young and adult mice subjected to sleep deprivation modeling. This suggests that HIF1α is involved in short-term rather than long-term adaptive processes to the effects of chronic stress.

The influence of sleep deprivation modeling also did not lead to significant changes in PLIN2 expression level in brain cells. However, PLIN2 alterations were depended on the animals’ age. The PLIN2 expression level in the brain of mice of 7-9 of age from both the “Control” and “SD” group was 1.04 ± 0.19 and 1.05 ± 0.78, respectively, which significantly exceeded the values of young specimens. Thus, our data are consistent with the previous studies showing the importance of PLIN2 identification as a marker for assessing age-related brain changes.

Alterations in the level of DNA methylations under sleep deprivation influence

To assess the changes in cellular metabolic rate and physiological state of mice and the renewal capacity of cells during aging and sleep deprivation influence, a method for registration of DNA chain damages was used.

The data showed a downward tendency in the percentage of the methylated DNA in both young (comet score: “SD young” 38.22 ± 1.17%) and adult (comet score: “SD adult” 33.14 ± 1.99%) mice exposed to sleep deprivation modeling (Figure 7).

It could be assumed that a decrease in the level of DNA methylation aggravated with age implies the emerging risk of depletion in the adaptive capacity of the organism, as was shown in particular in our comprehensive study.

Ethics statement

The experiments were carried out on female C57BL/6 mice (n=77). All experimental protocols used in the study were approved by the Bioethics Committee of Lobachevsky University and carried out in accordance with Act708n (23.08.2010) of the Russian Federation National Ministry of Public Health, which states the rules of laboratory practice for the care and use of laboratory animals, and the Council Directive 2010/63 EU of the European Parliament (September 22, 2010) on the protection of animals used for scientific purposes.

Experimental design

Female C57BL/6 mice were divided into the following groups: 1) Intact animals (n=13); 2) Control – the animals undergoing training in the Morris water maze without sleep deprivation modeling (n=32); 3) SD – the animals undergoing training in the Morris water maze followed by sleep deprivation modeling (n=32). Each group consisted of 1.5 (young) and 7-9 (adult) months mice.

Before starting the experiment, mice were weighed and then tested in the Morris water maze setup (Figure 8). As the Morris water maze test is associated with considerable physical activity, the “Intact” group was added to the experiment to evaluate its contribution to the studied parameters. The next day after the last training, sleep deprivation modeling was performed. Afterwards, the mice were re-weighed, and their general locomotor and orienting-exploratory activity were assessed in the “Open Field” setup. Besides, we analyzed the long-term memory retention in mice by testing them in the Morris water maze without a platform for 1 min. Then the murine brains were collected for further registration of mitochondrial functional activity, the HIF-1α (Hif1) and Plin2 genes expression level (RT-qPCR analysis) and histological analysis. The level of DNA methylations was assessed in the blood samples.

Sleep deprivation model

Animals were stressed using the flowerpot method, first used by M. Jouvet and colleagues to modulate deprivation of REM stage of sleep [49], with modifications. The experiments began daily at 10-11 a.m. A platform (d=3 cm) was located 1-2 cm below the water filling the circular pool. Each animal was placed on the platform and kept awake for 10 hours a day for five days. For the following five days, the mouse spent on the platform for 11 hours a day and additionally received sound signals every hour starting at 5 a.m.

“Open field” test

The general locomotor and orienting-exploratory activity of the experimental animals were tested in the “Open Field” setup (OpenField LE800S; Panlab Harvard Apparatus, Spain) before and a day after sleep deprivation modeling. Behavioral reactions were registered by a Sony SSC-G118 (Japan) camera for 5 min. The obtained data were analyzed in a Smart 3.0.03 software program (Panlab Harvard Apparatus, Spain; Stoelting, USA). The following behavioral reactions of mice were analyzed: 1) an orienting-exploratory activity (the number of squares crossed around the arena perimeter, the number of peeks in the holes, the number of upright postures); 2) emotional state (the number of squares crossed in the arena center, the residence time in the arena center); 3) passive reaction fear (frequency of grooming acts and the number of boluses).

Morris water maze test

To assess spatial learning and working memory of mice, the Morris Water Maze test with modifications was used [80, 81]. The test was conducted in a green circular pool (d = 900 mm, h = 500 mm) filled with opaque water (24±1° C) in which a white Plexiglas platform (d = 7.6 cm) was placed 1-2 cm below the water surface. The mice were trained for 5 days. Each session was 3 times for 60 min. The animal was trained to find the platform by an external visual landmark by placing it from different pool sides. If the mouse could not find the platform by the end of session time or jumped from the platform, it was forced to stand on it. The long-term memory retention was assessed by testing animals in a pool without a platform for 1 min. Data collection was automated using Smart Tracking (Panlab Harvard Apparatus, Spain; Stoelting, USA). The time of staying in a zone where the platform was previously located, and the type of strategy for searching the platform were assessed.

Registration of brain mitochondrial functional activity

Brain mitochondria were isolated using the standard differential centrifugation method [82]. Oxygen consumption by the isolated mitochondria was registered polarographically using a high-resolution respirometer Oxygraph-2k (Oroboros, Austria) in a closed chamber at constant stirring and controlled temperature (37° C). Incubation medium for mitochondria contained 120 КCl mM, 5 NaH2PO4 mM, 10 HEPES, 5 mM glutamate, 5 mM malate, and 14 mM MgCl2 (pH 7.4). The concentration of mitochondrial protein in a chamber measured by the Bradford method was 0.5 mg/ml.

The functional state of the mitochondrial respiratory chain was assessed according to the following parameters (Figure 9): a) V4 — the rate of oxygen consumption by the mitochondria at high content of substrates 5 mM glutamate and 5 mM malate (substrates of complex I) in the incubation medium; b) V3 — oxidative phosphorylation rate in V4 conditions supplemented with 5 mM adenosine diphosphate (ADP). The intensity of complex II of the respiratory chain was assessed after complex I inhibition by 0.5 μM rotenone and complex II stimulation with 10 mM sodium succinate.

RNA extraction and RT-qPCR

The expression level of HIF-1α (Hif1) and Plin2 genes was analyzed by quantitative real-time PCR. Total RNA was extracted from the mouse brain using ExtractRNA (Evrogen, Moscow, Russia). Then cDNA was synthesized using the MMLV reverse transcriptase kit and a random primer (Evrogen, Moscow, Russia). Amplification was carried out in real-time PCR using the qPCRmix-HS SYBR kit (Evrogen, Moscow, Russia) on an Applied Biosystems 7500 RT-PCR amplifier. The following pairs of primers were used:

Hif1a_fw1 - 5'-GCAATTCTCCAAGCCCTCCAAG-3';

Hif1a_rv1 - 5'-TTCATCAGTGGTGGCAGTTGTG-3';

Plin2_fw-5'-AAGCTGGAGCCACAAATTGC-3';

Plin2_rv - 5'-TGGCACTGGCAACAATCTCG-3';

Oaz1_fw - 5'-AAGGACAGTTTTGCAGCTCTCC-3';

Oaz1_rv - 5'-TCTGTCCTCACGGTTCTTGGG-3';

Data processing was carried out using the ΔΔCt method and a reference sample in which the target gene level was taken as a unit. Normalization was performed relative to the reference gene (Oaz1).

Brain morphology assessment

For histological studies, the brains isolated from experimental animals were fixed in a 10% formalin solution for 24 h at room temperature. For the next 24 h, the samples were placed in a 15% sucrose solution followed by incubation in a 30% sucrose solution for 24-48 h. After that, the brain was placed on a platform of freezing sliding cryostat Leica CM1520 (Leica, Germany) and gradually filling with cryogel (Leica, Germany) at 30° C. Next, the sample was cut into 10 μm thin coronal sections. Every fifth section was mounted on a glass slide and dried in the air for 24 h. The sections were then stained by the hematoxylin-eosin method [83]. Then, the sections were dehydrated in alcohols of upward concentration, purified in xylenes and embedded in a mounting medium (Consul-Mount, USA). The samples were examined using a Zeiss Primo Star light microscope (Germany) with integrated an Axio CamMRc camera (Zeiss, Germany).

DNA-comets

Analysis of DNA methylation was performed using a comet test developed by Wentzel and colleagues [84] with some modifications.

Aliquots of blood samples were mixed with 0.5% agarose (low melting point) and then placed on a glass slide pre-treated with 1% agarose (high melting point). The cells were stored in a buffer (2.5 M NaCl, 0.4 mM Na₄EDTA, 10% DMSO, 1% Triton X-100 (pH 8)) at 4° C overnight. Next, the slides were washed in a buffer containing 10 mM NaCl, 2 mM EDTA, 10 mM Tris-HCl, 1 mM B-mercaptoethanol (pH 7.9). Each slide was then treated with HpaII or MspI enzyme mixture (15 U/mL, CutSmart Buffer), covered with a coverslip and incubated in a humid chamber for an hour at 37° C. Electrophoresis was carried out in a 1.0 V/cm, 300 mA, 4° C regimens for 45 min. The slides were then fixed in ethanol, stained with DAPI (1 μg/ml) and examined in an LSM 800 confocal microscope (Zeiss, Germany). Electrophoresis leads to the formation of comet-like structures, and using fluorescence microscopy, the number of DNA breaks can be analyzed by the intensity of brightness of the comet tail [85].

For each sample, 100 cells were counted, and the percentage of DNA in comet tails (Tail DNA, %) was determined. The percentage of CpG dinucleotides methylation was calculated using CometScore 2.0 software and the following formula:

$100-\frac{\%T Hpall}{\%T Mspl}\times 100$ (1)

where % T HpaII and % T MspI - are the average percentage of tails in a slide treated with the corresponding enzyme.

Statistical data analysis

The quantified data are presented as the mean ± standard error of the mean (SEM). GraphPad Prism (v.9.0) was used for statistical analysis. The Shapiro-Wilk test was used for normal distribution analysis. Differences between two independent groups were assessed by using the Mann-Whitney test. In order to determine the equality of the mean values in the two groups, the Wilcoxon T-test was applied. The Kruskal-Wallis test was used to assess the equality of medians of several groups. Differences between groups were considered significant if the corresponding p-value was less than 0.05.