The relationship between gut microbiota and inflammatory response, learning and memory in mice by sleep deprivation

A total of 30 male 8-week-old C57BL/6J mice (No. SCXK (Yv) 2020-0005) were obtained from Henan Skbex Biotechnology Co. LTD. (Anyang, China). Mice were housed in the Medical Animal Center at the College of Public Health of Zhengzhou University under the control environment (22 ± 2°C, 45%-60% relative humidity), with a regular 12h light/12h dark cycle. The light was turned on at 8:00 and turned off at 20:00. After two weeks of acclimation, the mice were randomly divided into three groups: regular control group (RC, n=10), environmental control group (EC, n=10), and sleep deprivation group (SD, n=10). The sleep deprivation mice model was established using a Modified Multiple Platform Method (De Lorenzo et al., 2018). This method takes advantage of mice’s fear of water and places them in the sleep deprivation box. When they enter the sleep stage, their whole-body muscles will relax and wake up after falling into the water, which could realize the purpose of sleep deprivation (Machado et al., 2004). The experimental period was 8 weeks (Poroyko et al., 2016). RC mice were kept in ordinary cages during the experiment. EC mice were subjected to the environmental control box for 6 hours a day (from 8:00 to 14:00). Sleep deprivation mice were deprived of 6 hours of sleep a day in the sleep deprivation box (from 8:00 to 14:00) (Rothman et al., 2013; Saito et al., 2014). The water temperature in the box was kept at 20 to 22°C, and the water was changed once every 24 h. Food and water were given ad libitum and measured every 3 d throughout the experiment. The body weights of mice were recorded weekly. All mice had free access to food, water, and movement during this period (Figure 1).

The Morris water maze (MWM) was used to assess spatial learning and memory (Vorhees and Williams, 2006; Murayama et al., 2021). Mice were tested for 6 consecutive days in each trial: visible test at 1-5 days, hidden test for 6 days. The maze consisted of a round steel tank (120 cm in diameter, 30 cm in height) filled with warm water (22°C) and white nontoxic titanium dioxide added to render it opaque. The pool was divided into four quadrants (I, II, III, and IV). A white escape platform with a diameter of 8 cm was placed at a fixed location in quadrant III and submerged about 1 cm below the water surface (Figure 2A). The following experiments were conducted at 8:00. Experiment was always performed at the same time under the same environmental conditions. Each mouse was placed in the water in all four quadrants in a fixed order to perform four training trials per day. The interval between the two training sessions should be 15~20 min. The positioning sailing experiment should be carried out for 5 consecutive days, and latency to reach the hidden platform was measured in each mouse. The maximum trial duration was 60 s. Animals that failed to locate the hidden platform were manually guided. Once they reached the platform, they were allowed to remain there for 15 s. Memory consolidation was assessed on day 6. The platform was removed during the test, and each mouse could swim freely for 60 s (Figure 2B). The time of exploration, traversing times in the original platform, swimming distance, and swimming time in the target quadrant was recorded. The animal movement was tracked using the SuperMaze behavioral monitoring system (XR-Xmaze; Shanghai Xinruan Information Technology Co. Ltd.).

IL-1β, IL-6, and TNF-α serum concentrations were determined using an enzyme-linked immunosorbent assay (ELISA). The orbital vein blood extraction method was used to make the blood flow from the orbit into the EP tube, and the volume was 0.6-1.0 mL per sample. After 30 min at room temperature, the serum and red blood cells were rapidly separated by centrifugation at 3000 r/min for 10 min. The specific detection process follows the manufacturer’s instructions.

Total genomic DNA was extracted from fresh fecal samples at the end of 8 weeks by using the QIAamp DNA Stool Mini Kit (Qiagen, Germantown, MD, USA) according to the manufacturer’s instructions (the fecal samples in each group were randomly selected, fecal weight >150 mg per sample, n=5 per group). The 16S rRNA of the V3-V4 area was amplified with thermal cycling, which is 2 min at 94°C, followed by 24 cycles of 30 s at 94°C, 30 s at 55°C, and 30 s at 72°C, and a final extension at 72°C for 5 min. The 16S rDNA high-throughput sequencing was carried out using the Illumina Miseq platform at TinyGene Bio-Tech Co.Ltd (Shanghai, China). Trimmed high-quality reads were clustered into Operational Units based on a >97% sequence similarity identity by UCLUST. The Silva 132 database was used as a reference for annotating taxonomic information for each sequence. Linear discriminant analysis effect size (LEfSe) was conducted to identify the biomarker species in different groups using metastats software.

Data were analyzed using SPSS 25.0 and GraphPad Prism 8 software. Results were presented as Mean ± Standard Deviation. ANOVA followed by Tukey’s test assessed differences among more than two groups. T-test was used for the comparison of statistical significance between groups. Pearson correlation analyses analyzed the correlations of study variables. P values <0.05 were considered to be statistically significant.

The latency to reach the platform of SD mice was more prolonged than RC and EC mice during the five-day positioning navigation experiment (Table 1), and there were statistically significant differences on the 2nd, 3rd, 4th, and 5th days (p<0.05). In the space exploration experiment (Figure 3), compared with RC and EC mice, the exploration time of SD mice was extended, but there were no statistically significant differences (p>0.05). When the hidden platform was removed, there was a significantly decreased traversing times, swimming distance, and swimming time in the target zone (p<0.05). In the positioning navigation and space exploration experiments, there was no statistically significant difference between RC and EC mice (p>0.05). The swimming paths of three groups of mice in MWM showed that only SD mice had impaired spatial memory (Figure 4). These results suggested that sleep deprivation has impaired the cognitive function of mice.

As shown in Figure 5, the detection of pro-inflammatory cytokines showed that compared with the RC and EC mice, the serum levels of IL-1β, IL-6, and TNF-α were increased by 69.28%, 61.18%, and 50.76% due to sleep deprivation, respectively, with significant significance (p<0.001). However, there were no significant differences in serum levels of pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α) between RC and EC mice (p>0.05). These results suggested that sleep deprivation can increase mice’s serum levels of pro-inflammatory cytokines.

Figure 6 showed that Muribaculaceae, Lachnospiraceae, Ruminococcaceae, Bacteroidaceae, Prevotellaceae, Akkermansiaceae, Rikenellaceae, Erysipelotrichaceae, Burkholderiaceae, Tannerellaceae were top 10 in the family classification. The abundance of Burkholderiaceae and Tannerellaceae in SD mice increased by 1.8 times and 3 times, respectively, while the abundance of Ruminococcaceae, Prevotellaceae, Rikenellaceae, and Akkermansiaceae decreased by 52.9%, 41.7%, 59.3%, and 68.4%, respectively.

As shown in Figure 7, 4 biomarkers were detected in SD mice. The abundance of Tannerellaceae, Rhodospirillales, Alistipes, and Parabacteroides increased significantly. However, Ruminococcaceae_UCG_013, Lachnospiraceae_NK4A136_group, Lachnospiraceae_bacterium_DW17, Ruminococcaceae_UCG_010, and Eubacterium_xylanophilum_group were more abundant in EC mice.

As shown in Table 2, IL-1β was positively correlated with the abundance of Muribaculaceae (r=0.497, p<0.05) and negatively correlated with the abundance of Lachnospiraceae and Akkermansiaceae (r=-0.583, r=-0.272, p<0.05). TNF-α was positively correlated with the abundance of Erysipelotrichaceae, Burkholderiaceae, and Tannerellaceae (r=0.492, r=0.646, r=0.726, all p<0.05) and negatively correlated with the abundance of Akkermansiaceae (r=-0.254, p<0.05).

In this study, the MWM results showed that sleep deprivation could impair the learning and memory of mice. Tuan and Lee (2019) adopted the modified multiplatform method to conduct 72-hour paradoxical sleep deprivation in mice. They found that sleep deprivation adversely affected short-term memory in a novel object recognition test, consistent with this study (Tuan and Lee, 2019). Lack of sleep will likely lead to cognitive dysfunction, especially the impact on attention (Cairney et al., 2015). Vigilant attention is a significant component of a wide range of cognitive performance, and a decrease in vigilant attention can increase the variability of the stress response. Sleep deprivation can aggravate this change (Hudson et al., 2020). AD is a devastating and irreversible cognitive impairment and the most common type of dementia. Along with progressive cognitive impairment, dysfunction of the circadian rhythms also plays a pivotal role in the progression of AD (Uddin et al., 2020). Xu also proved that sleep problems (insomnia, fragmentation, daytime dysfunction, prolonged latency, rapid eye movement sleep disorder, and excessive time in bed) were associated with a higher risk of cognitive impairment; sleep management might serve as a promising target for AD prevention (Xu et al., 2020). Disrupted sleep and circadian rhythms could increase amyloid-β (Aβ) production and decrease Aβ clearance rate (Ning and Jorfi, 2019). Moreover, acute sleep deprivation could increase tau levels in interstitial fluid. In contrast, chronic sleep deprivation could accelerate the spread of tau aggregation in neural networks (Holth et al., 2019), which leads to a decline in cognitive function and accelerates the development of AD. Several reports have also reported that decreased levels of brain-derived neurotrophic factor (BDNF) in the systemic circulation were associated with sleep disturbances (Fan et al., 2019; Furihata et al., 2020; Rahmani et al., 2020). BDNF and its receptors are widely expressed in the nervous system and play an essential role in increasing synaptic plasticity, promoting neurogenesis, and the development, differentiation, growth, and regeneration of neurons (Schinder and Poo, 2000). BDNF is involved in numerous cognitive functions, including learning and memory, and is essential for forming long-term memories (Avgan et al., 2017). These findings provide a scientific basis for new therapies to reduce the risk of cognitive dysfunction by improving sleep quality and developing ways to delay the disease in cognition impairment.

Although there was no significant change in microbial composition between the two groups, the relative abundance of bacteria in Prevotellaceae, Rikenellaceae, and Akkermansiaceae was slightly reduced compared to the control group, the relative abundance of Enterobacteriaceae and Erysipelotrichaceae was slightly increased. The human intestinal Akkermansiaceae family maintains intestinal integrity (Geerlings et al., 2018) and can degrade mucin. It negatively correlates with obesity, diabetes, inflammation, and metabolic disorders (Depommier et al., 2019). Gastrointestinal inflammatory diseases are frequently associated with dysbiosis, characterized by changes in gut microbial communities that include the expansion of facultative anaerobic bacteria of Enterobacteriaceae (Phylum Proteobacteria). Dysbiotic expansion of Enterobacteriaceae during gut inflammation could be prevented by tungstate treatment, which selectively inhibited molybdenum-cofactor-dependent microbial respiratory pathways that are operational only during episodes of inflammation (W. Zhu et al., 2018). The changes in the intestinal microbial ecosystem are related to the metabolic syndrome of most obese individuals. Studies have found that the intestinal contents of Erysipelotrichaceae in mice with abnormal metabolism were high, paralleled by increased expression of IL-1, IL-4, IL-6, IL-17, and IFN-γ (Pindjakova et al., 2017). Many gut microbiotas are closely related to the regulation of inflammation, and changes in the intestinal microflora caused by antibiotics could reduce the inflammatory response through metabolic status. Sun found that antibiotic exposure can significantly increase the bacterial abundance of Prevotellaceae and Rikenellaceae (Sun et al., 2019). These changes in gut microbiota can affect the inflammatory response, which is consistent with the results of this study and provides new insights into the integration of the complex network of interactions between gut microbiota and host inflammatory response.

In this study, LEfSe suggested that sleep deprivation could change the structure and composition of intestinal microflora in mice, and the abundance of microorganisms such as Tannerellaceae, Rhodospirillales, Alistipes, and Parabacteroides was significantly increased in the SD mice. However, the Ruminococcaceae_UCG_013, Lachnospiraceae_NK4A136_group, Lachnospiraceae_bacterium_DW17, Ruminococcaceae_UCG_010, and Eubacterium_xylanophilum_group were more enriched in EC mice. Many studies have shown that sleep deprivation can affect gut microbiota composition, but different studies suggest differences in the abundance of microbiota. Park showed that sleep deprivation could reduce Lactobacillaceae’s contents and increase Erysipelotrichaceae and Enterobacteriaceae contents (Park et al., 2020). Benedict demonstrated that sleep deprivation could increase the content of Coriobacteriaceae and Erysipelotrichaceae and decrease the content of Tenericutes (Benedict et al., 2016). The results of this study need to be more consistent with previous studies. Studies have found that Parabacteroides_distasonis is extremely important in SD mice, but it is one of the core bacteria in humans. Its content is negatively correlated with obesity, diabetes, and other disease states, suggesting that bacteria may positively regulate glucose and lipid metabolism (Liu S. J. et al., 2020). Further research and analysis are needed on the contradictions.

Other findings are consistent with previous research. Adriansjach found that changes in lifestyle, inflammation, and immune function could increase Alphaproteobacteria (Adriansjach et al., 2020). Alistipes is a relatively new genus of bacteria closely associated with inflammation, cancer, and mental health (Parker et al., 2020). Some studies have found that Alistipes has a noticeable pro-inflammatory effect, which can increase the number of Th17 cells and reduce the number of bacteria producing butyrate (Jama et al., 2019), which suggests that this species is a potential driving factor for intestinal barrier dysfunction and inflammation in patients with hypertension (Kim et al., 2018). Moreover, studies have shown that Alistipes can disrupt the gut-brain axis and reduce the utilization rate of serotonin. Tryptophan is a precursor of serotonin, the decrease of which is associated with depression (Kim et al., 2018). Silveira-Nunes found that serum levels of tumor necrosis factor and interleukin-6 increased in patients with hypertension, while the relative abundance of Lactobacteriaceae and Ruminococcaceae decreased significantly (Silveira-Nunes et al., 2020). Lachnospiraceae plays a vital role in reducing oxidative stress and preventing inflammation. Darnaud found that regenerative islet-derived protein 3α can change the colon microflora by decreasing the level of reactive oxygen species (improving the survival rate of Lachnospiraceae), thus improving inflammatory bowel disease (Darnaud et al., 2018). As a result, sleep deprivation can lead to an imbalance in gut microbiota, lower levels of probiotics, and high levels of harmful bacteria. This study linked sleep deprivation to the gut microbiome to identify bacterial groups sensitive to sleep disorders that could be targeted for treatment to improve sleep inadequacy for health maintenance.

The abundance of Muribaculaceae, Erysipelotrichaceae, Burkholderiaceae, and Tannerellaceae in mice was positively correlated with the levels of pro-inflammatory cytokines. The abundance of Akkermansiaceae and Lachnospiraceae was negatively correlated with the levels of pro-inflammatory cytokines. Contrary to previous studies, Muribaculaceae is a dominant Bacteroidales in mice, and it is negatively correlated with apoptosis of epithelial cells and IL-6 (Meng et al., 2019). However, this study found that Muribaculaceae can promote inflammation, which needs further research to explore. Although no studies have directly investigated the relationship between Erysipelotrichaceae and inflammation, some studies have found that the absence of congenital immune receptor NLRP12 can make mice prone to obesity, decrease insulin sensitivity and increase adipose tissue inflammation. The obesity-related Erysipelotrichaceae is significantly increased (Truax et al., 2018). Burkholderiaceae is a pathogenic bacterium. Studies have found that Burkholderiaceae can aggravate the inflammatory response of patients with cystic fibrosis and cause fatal lung infections (Mesureur et al., 2017). Tannerellaceae are oral pathogenic bacteria, and most studies focus on their relationship with oral diseases such as chronic periodontitis. The detection rate of Tannerellaceae at the lesion sites of periodontitis is relatively high, so Tannerellaceae can promote the occurrence of inflammation (Yang et al., 2007). Cao and Lang supported the results of this study, both of which found that Akkermansiaceae and Lachnospiraceae could be reduced due to inflammation (Cao et al., 2020; Lang et al., 2020).

Given that the gut microbiome interacts with pro-inflammatory cytokines, this study also sought to explore whether there is a link between inflammatory responses and gut microbes and sleep. Li found that insomnia symptoms, gut microbes, and inflammation may be related in a complex way (Li et al., 2020). Sleep is an important phenomenon related to central and peripheral immune regulation, and studies have pointed out that lack of sleep can cause mild systemic inflammation, characterized by the release of cytokines, chemokines, and acute inverse proteins, which also supports the results of this study (Hurtado-Alvarado et al., 2016). Sleep deprivation mediated inflammation may be associated with mild to moderate damage to multiple organs, adversely affecting cardiovascular and gastrointestinal health (Periasamy et al., 2015). Intestinal microbiota plays an essential role in the occurrence and development of various clinical manifestations, especially those related to the gastrointestinal tract. Evidence such as fecal transplantation to prevent inflammatory enteritis recurrence and broad-spectrum antibiotics from improving colitis supports this view (Man et al., 2011). The inflammasome regulates the composition of intestinal microbes, suggesting that the inflammatory-intestinal microbial axis may be the core of the occurrence and development of intestinal inflammation, cancer, and metabolic syndrome (Man, 2018). Sleep deprivation can cause inflammation, and pro-inflammatory cytokines can change the composition and abundance of intestinal microbes. Therefore, the intestinal microbiome can be used as an essential indicator to assist in the diagnosis of insomnia and provide a new target for treating sleep disorders.

This study found that chronic sleep deprivation had subtle effects on the gut microbiota of mice, providing a scientific basis for explaining the psychological problems caused by sleep disorders. Nevertheless, it is worth further exploring in more extensive studies, and by extension in population, to assess how sleep deprivation affects personal gut microbiota. Prospective and experimental studies are needed to confirm the possible links between sleep, gut microbiota, and cognition and to determine whether improving gut microbiota can relieve cognitive decline associated with sleep disorders. Another limitation is the current study design resulting that we could not get results that SD mice demonstrated whether resilience in their impairment of gut microbiota composition, immune function, and cognitive function after the finish of the protocol. Previous research has shown that sleep deprivation worsens inflammation and delays recovery in a mouse model of colitis (Tang et al., 2009). Moreover, sleep deprivation impairs learning-induced increases in hippocampal sharp wave ripples and associated spike dynamics during recovery sleep (Li et al., 2022). Therefore, we would analyze the gut microbiota, proinflammatory factor, and cognitive function in SD mice during sleep recovery in the subsequent experiments.