The effects of esketamine on the intestinal microenvironment and intestinal microbiota in mice

Abstract

Objective

This study aimed to investigate the impact of esketamine on the intestinal flora and microenvironment in mice using mRNA transcriptome sequencing and 16S rRNA sequencing.

Methods

Ten female mice were randomly assigned to two groups. One group received daily intramuscular injections of sterile water, while the other group received esketamine. After 24 days, the mice were sacrificed, and their intestinal tissues and contents were collected for 16S rRNA sequencing and mRNA transcriptome sequencing. The intergroup differences in the mouse intestinal flora were analyzed. Differentially expressed genes were utilized to construct ceRNA networks and transcription factor regulatory networks to assess the effects of esketamine on the intestinal flora and intestinal tissue genes.

Results

Esketamine significantly altered the abundance of intestinal microbiota, including Adlercreutzia equolifaciens and Akkermansia muciniphila. Differential expression analysis revealed 301 significantly upregulated genes and 106 significantly downregulated genes. The ceRNA regulatory network consisted of 6 lncRNAs, 44 miRNAs, and 113 mRNAs, while the regulatory factor network included 13 transcription factors and 53 target genes. Gene Ontology enrichment analysis indicated that the differentially expressed genes were primarily associated with immunity, including B-cell activation and humoral immune response mediation. The biological processes in the ceRNA regulatory network primarily involved transport, such as organic anion transport and monocarboxylic acid transport. The functional annotation of target genes in the TF network was mainly related to epithelial cells, including epithelial cell proliferation and regulation.

Conclusion

Esketamine induces changes in gut microbiota and the intestinal microenvironment, impacting the immune environment and transport modes.

Introduction

Ketamine is an organic compound with the formula (+/−) 2-(2-chlorophenyl)-2-(methylamino)-cyclohexanone, with a molecular weight of 274.4 and the chemical formula C₁₃H₁₆ClNO. Since 1970, ketamine has been used in therapeutic settings. ¹ In addition to its best-known dissociative anesthetic properties,^2,3 it exerts analgesic, ⁴ anti-inflammatory, ⁵ and antidepressant effects. ⁶ Although (S)-ketamine and (R)-ketamine (or esketamine and arketamine) are both enantiomers of ketamine, ⁷ esketamine has a greater binding affinity for NMDA receptors. Consequently, it has more anesthetic and analgesic potency in humans than arketamine.^8–10 At the same time, previous evidence suggests that the use of ketamine or esketamine may induce many side effects, for example, dizziness, dissociation, nausea, and headache;^11–13 rapid intravenous injection can cause transient apnoea and increase the incidence of laryngospasm, ¹⁴ and drug abuse may also trigger cystitis and bladder contraction syndrome. ¹⁵

The intestinal microbiota consists of thousands of microorganisms, including bacteria, viruses and some eukaryotes, and is a complex community of microorganisms living in the human and animal digestive tract.^16,17 The intestinal microbiota plays an important role in maintaining normal intestinal physiology and health by enhancing the immune system, ¹⁸ controlling the proliferation and differentiation of epithelial cells, ¹⁹ influencing neurological function, ²⁰ and promoting digestion and metabolism ²¹ in the human body. Along with the advancement and improvement of bioinformatics technologies such as high-throughput sequencing and metagenomics, the accuracy and convenience of gut flora detection technologies have promoted the study of intestinal flora. Gut flora dysbiosis has been found to present correlations with a variety of diseases, such as cardiovascular system diseases, obesity, inflammatory bowel disease, nonalcoholic steatohepatitis, and metabolic diseases.^22–26 In addition, disorders of the gut microbiota are also associated with immune pathologies such as allergies and autoimmune diseases.^27,28 Several researchers have reported that diet, ²⁹ age, ³⁰ antibiotics, ³¹ and drugs ³² such as lipid-lowering statins, laxatives, metformin, β-blockers and selective serotonin reuptake inhibitor antidepressants can alter the composition and function of the intestinal microbiota. However, little attention has been devoted to the effects of esketamine on gut microbiota and gene expression in intestinal tissues.

Our study aimed to determine the effects of continuous esketamine administration on the intestinal microbiota and the expression of intestinal genes in mice. To test this, we used 10 female SPF-grade C57BL/6 mice that were intramuscularly injected with 0.05 mL/10g esketamine diluted to 4 mg/kg or the same volume of sterile water every day for 24 days. Subsequently, the intestine and intestinal contents were subjected to RNA transcriptome sequencing and 16S rRNA sequencing, followed by other bioinformatics analyses.

Materials and methods

Animals and drugs

Ten female 4 to 6-weeks-old SPF C57BL/6 mice (weight, 20 ± 2g) were purchased from Zhejiang Vital River Laboratory Animal Technology Co., Ltd (Jiaxing, Zhejiang, China) with the production licence SCXK (京) 2021-0006. After purchase, they were kept in the SPF-grade animal house at Shanghai University of Medicine & Health Sciences for 7 days. The temperature in the animal house was kept at 20°C–25°C, and the relative humidity was 40%–70%. The cages, feed, water and bedding were autoclaved, and the external environment of the rearing cages was disinfected every 7 days. Esketamine, a clear liquid, was diluted to 4 mg/kg using sterile water.

Animal experimental procedures

Ten mice labelled using the toe clipping method were randomly divided into 2 groups (n = 5 per group): the continuous esketamine treatment group (ET group, 4 mg/kg) and the sterile water control group (NC group). Mice were housed 4 in cage 1, with 2 mice in the ET group and the other 2 mice in the NC group to act as in-cage controls. Similarly, cage 2 housed 6 mice, 3 mice from the ET group and 3 mice from the NC group. In total, the experiment was conducted for 24 days, and all mice were weighed once a week. Both groups of mice were injected intramuscularly every day with 0.05 mL/10g per injection. After 24 days, the mice were sacrificed and dissected, and samples of intestinal contents and intestinal tissues were collected in 2 mL EP tubes and stored in liquid nitrogen. At the end of the experiment, the samples were transferred from the liquid nitrogen tank to a -80°C freezer for storage. Unfortunately, one mouse from the ET group died due to mishandling of the injection and was not included in the analysis.

Data collection from samples

RNA transcriptome sequencing of the samples was performed on the Illumina NovaSeq 6000 sequencing platform by Shanghai Majorbio Bio-Pharm Technology Co., Ltd (Shanghai, China). Sequencing of 16S rRNA and microbial diversity-related analyses, such as clustering analysis of operational taxonomic units (OTUs), alpha and beta diversity analysis and statistical analysis of microbial multivariate variables, were executed by Shanghai OE Biotech Co., Ltd (Shanghai, China).

Identification of differentially expressed genes

The R package “DESeq2” was used for differential gene analysis between the ET group and NC group, and |logFC| > = 1 and p value <.05 were used as screening criteria for differential mRNAs.

Construction of a ceRNA regulatory network

The miRNA‒mRNA and miRNA‒lncRNA interactions of mice were obtained from the Encyclopedia of RNA Interactomes (ENCORI, http://starbase.sysu.edu.cn) database. The ceRNA (lncRNA‒miRNA) regulatory network was constructed according to intersections with DEGs, which were visualized by using Cytoscape (version 3.7.2, http://cytoscape.org). In addition, the biological processes involved in DElncRNAs were revealed by functionally annotating the target mRNAs in the ceRNA network.

Construction of the transcription factors network

The Transcriptional Regulatory Relationships Unravelled by Sentence-based Text mining (TRRUST, https://www.grnpedia.org/trrust/) database contains 8444 and 6552 TF-target regulatory relationships of 800 human TFs and 828 mouse TFs. In this study, DEmRNAs as TFs and their targets were screened, and the transcription factor (TF) network was visualized by Cytoscape.

GO enrichment analyses

GO (http://geneontology.org/) enrichment analysis of DEGs, target genes in the TF regulatory network, and DEmRNAs in the ceRNA network was performed using the “clusterProfiler” package in R software. The results were visualized as chord diagrams, network diagrams, and bubble charts using the “GOplot” package, “enrichplot” package, and “graphics” package, respectively.

Statistical analysis

Statistical analyses of all data were processed by R software (Version 4.0.2) (^∗p < .05, ^∗∗p < .01, ^∗∗∗p < .001), and statistical significance was determined at p < .05. All p-values utilized in this study have been adjusted for multiple comparisons, and the p-value correction method used is Benjamini-Hochberg (BH). Genes with p < .05 and |Log₂fold change (FC)| > 1.0 were considered as significantly differential expressed mRNAs (DEmRNAs). Using Bray Curtis distance metrics, beta diversity analysis was carried out to examine the structural variance of microbial communities among samples, and principal coordinates analysis (PCoA) was used to display the results. The t test was used to estimate the changes in the intestinal microenvironment of the ET and CN groups at the species level and genus level.

Result

Body weights

The analysis detected no significant change in weight between the groups (p = .57) (Figure 1(b)). This suggests that esketamine does not affect body weight in mice.

Figure 1.

The process and results of the experiment. (a) Flowchart. (b) Mean weight of mice in the NC group and ET group (24 days).

Comparison of intestinal flora between the ET group and NC group

To assess the differences in microflora composition between the ET and NC groups, we performed PCoA (Figure 2(a)), which resulted in a significant difference between the two groups (p = .025). From the results, it is clear that esketamine altered the intestinal microflora of the mice. The overall differences in mouse intestinal flora between the ET and NC groups in terms of genus and species are shown in Figure 2(b) and (c). Specifically, at the species level, the abundance of Adlercreutzia equolifaciens and Akkermansia muciniphila was significantly elevated (Figure 2(d)). At the genus level, the abundance of Alloprevotella, Muribaculum, and UCG-009 decreased significantly in the ET group (t test, p-value <.05). Moreover, the abundance of Ruminococcus, Family_Xlll_AD3011_group, Adlercreutzia, and Akkermansia significantly increased (t test, p-value <.05) (Figure 2(e)).

Figure 2.

Analysis of differences between the ET group and NC group. (a) PCoA analysis, where the horizontal coordinate (PC1) and the vertical coordinate (PC2) are the two main coordinates with the greatest degree of explanation for the differences between samples; the same colour indicates the same group, and a point is a sample. (b) Heatmap of differences at the genus level, with sample information in the horizontal direction and species annotation information in the vertical direction; the species clustering tree is on the left side of the figure; clustering branch groups on top represent samples from different subgroups. Red indicates a higher relative abundance of species, and blue indicates a lower relative abundance of species. (c) Heatmap of differences at the species level. (d) Comparison of intestinal flora abundance between the ET group and NC group at the species level. Different colours represent different groups of samples, and the vertical coordinates indicate the relative abundance values of species. (e) Comparison of intestinal flora abundance between the ET group and NC group at the genus level.

Differential expression analysis and enrichment analysis between the ET group and NC group

By analysing the raw data of five samples from the NC group and four samples from the ET group, a total of 407 differentially expressed genes were obtained, including 301 upregulated genes and 106 downregulated genes (Figure 3(a)). Furthermore, GO enrichment analysis was performed for functional annotation of DEGs, and the results showed that the differentially expressed genes were mainly enriched in the B-cell receptor signalling pathway, phagocytosis recognition, classical pathway of complement activation, phagocytosis, engulfment, positive regulation of B-cell activation, humoral immune response mediated by circulation, plasma membrane invagination, membrane invagination, regulation of B-cell activation, etc (Figure 3(b)).

Figure 3.

Differentially expressed genes and functional analysis in intestinal samples. (a) Red genes represent significantly high expression in samples injected with high levels of ketamine, green genes represent significantly high expression in controls, and black genes indicate insignificant changes. (b) Biological processes involving differentially expressed genes.

CeRNA network and biological processes involving mRNAs of the ceRNA network

A total of 6 lncRNAs, 44 miRNAs and 113 mRNAs were constructed in the ceRNA network (Figure 4(a)). In other words, there were 6 lncRNAs targeting 44 miRNAs in the ceRNA network, and these 44 miRNAs target 113 DEmRNAs. A total of 113 mRNAs were then subjected to GO analysis and screened to determine their major enriched biological processes, which included organic anion transport, monocarboxylic acid transport, import into cells, carboxylic acid transport, organic acid transport, and anion transmembrane transport (Figure 4(b)).

Figure 4.

A ceRNA network and its functional analysis in intestinal samples. (a) The red, yellow, and cyan nodes represent differentially expressed lncRNAs, miRNAs, and differentially expressed mRNAs, respectively. (b) Biological processes involving mRNAs of the ceRNA network.

TF network and its functional analysis

Figure 5(a) illustrates the transcriptional regulatory network of differentially expressed genes, thus identifying the regulatory mechanisms of these genes. A total of 13 of these differentially expressed genes acted as regulatory factors targeting the other 53 genes. These 13 transcription factors are Creb3l1, Creb3l4, Dlx2, Epor, Etv4, Etv5, Glis3, Hoxa3, Mkx, Nr4a1, Nupr1, Setbp1 and Shh. Functional analysis was performed on these 53 target genes, and their enriched biological functions were obtained, as shown in Figure 5(b). These include epithelial cell proliferation, regulation of epithelial cells, muscle cell proliferation, response to hypoxia and response to oxygen levels.

Figure 5.

TF network and its functional analysis in intestinal samples. (a) The yellow and cyan nodes represent transcription factors and their targets, respectively. V-shaped and elliptical nodes represent differentially and nondifferentially expressed genes, respectively. The different coloured edges represent different modes of regulation. Red, green and black represent activation, repression, and unknown, respectively. (b) Biological processes involving target genes of the TF network.

Discussion

Ketamine is composed of two isomers, namely esketamine and arketamine, with esketamine being more extensively utilized in clinical settings as a therapeutic agent. Consequently, this investigation specifically focused on utilizing esketamine to explore its impact on the gut microenvironment and gut microbiota.

In-depth scrutiny of 16S rRNA transcriptomic data uncovered notable modifications in the relative abundance of various gut microbial taxa subsequent to the administration of esketamine in mice. Specifically, the taxa affected encompassed Alloprevotella, Muribaculum, UCG-009, Ruminococcus, Family_Xlll_AD3011_group, Adlercreutzia, and Akkermansia. Adlercreutzia equolifaciens was isolated from human feces in 2008 ³³ and belongs to the genus Adlercreutzia. Adlercreutzia species convert dietary compound phytoestrogens to equol, ³⁴ which has beneficial effects on human health. ³⁵ Several studies have revealed a negative correlation between Adlercreutzia and inflammation-related diseases such as ulcerative colitis, ³⁶ inflammatory bowel disease, ³⁷ and multiple sclerosis. ³⁴ Notably, in another study, the abundance of Adlercreutzia was found to be positively correlated with neuroprotective genes and highly negatively correlated with inflammatory factors. ³⁸ The probiotic properties of Akkermansia muciniphila, belonging to the genus Akkermansia, including metabolic control, immunological regulation, and gut health protection, have been extensively studied since this species is a common inhabitant of both human and animal digestive tracts. ³⁹ Similarly, the abundance of Akkermansia muciniphila is also reduced in many inflammatory diseases.^40–42 In addition, the Akkermansia genus showed lower abundance in mice with Alzheimer's disease. ⁴³ Together, the present findings confirm that ketamine can achieve its effects by altering the composition of colonies containing Adlercreutzia, Akkermansia muciniphila, etc., in the intestinal tract.

GO enrichment analysis was performed on differentially expressed genes identified through mRNA transcriptomic sequencing. The results revealed that these differentially expressed genes were significantly enriched in biological processes predominantly related to the immune system, suggesting that administration of esketamine can alter the intestinal immune environment in mice. In line with previous studies, ketamine exerts its antidepressant effects by modulating the immune system, including peripheral inflammatory cytokines, central microglia, and astrocytes. ⁴⁴

Furthermore, the GO enrichment analysis of 113 mRNAs in the ceRNA network unveiled a predominant involvement of these mRNAs in biological processes associated with drug transport. Drug transport is the kinetic process of the absorption, distribution, metabolism and excretion of drugs from the body. This process is carried out by drug transport proteins, which are divided into ATP-binding cassette (ABC) transporter and solute carrier (SLC) transporter families. ⁴⁵ Organic anion transport, monocarboxylic acid transport, carboxylic acid transport, organic acid transport and anion transmembrane transport are all carried out by the SLC transporter family. ⁴⁶ SLC transporter proteins serve an important role in the physiological function of drug absorption. Therefore, we speculated that the intestinal absorption of esketamine was related to organic anion transporters, monocarboxylic acid transporters and carboxylic acid transporters. Experiments have proven that ketamine is the substrate of organic cation transporters, and organic cation transporters affect the absorption of oral ketamine. ⁴⁷

Among the 53 IF-targeted genes in the TF network, two genes exhibited differential expression in the experimental group, Il17f, which was activated by the regulator Etv5, and Slc1a4, which was inhibited by the regulator Creb3l1. Both Etv4 and Etv5 transcription factors belong to the E26 transformation-specific transcription factor superfamily. Tv4 is involved in cellular processes such as proliferation, differentiation and tumorigenesis.^48,49 Etv5 has been shown to play an important role in coordinating limb development ⁵⁰ and to regulate the epithelial-mesenchymal transition in many types of cancer. ⁵¹ Moreover, NR4A1 inhibits inflammatory signalling in the gastrointestinal tract, ⁵² thereby reducing the release of proinflammatory mediators in intestinal epithelial cells. ⁵³ In addition, it has been shown that the deletion of NR4A1 makes mice more prone to colonic fibrosis. ⁵⁴ Il17f encodes a protein that is a cytokine expressed by activated T cells. This cytokine is associated with normal immune responses and has been shown to stimulate the production of other cytokines including IL6, IL8 and CSF2/GM_CSF. In addition, this cytokine inhibits angiogenesis in endothelial cells. ⁵⁵ It is an effector cytokine of the innate and adaptive immune system, involved in antimicrobial host defence and maintenance of tissue integrity. ⁵⁶ Il17f is also a member of the IL-17 cytokine family, which contains six members (IL-17A-F). This family plays an important role in both normal immune responses and human immune diseases. For example, the IL-17 family may play a role in rheumatoid arthritis, ⁵⁷ psoriasis, ⁵⁸ and many other diseases mediated by abnormal immune responses. Interestingly, it has been demonstrated that IL-17 may indirectly alter central nervous system-directed autoimmunity by regulating the homeostasis of the intestinal flora. ⁵⁹ SLC1A4 (also known as ASCT1) belongs to the SLC1 family and transports sodium-dependent neutral amino acids such as serine, threonine, alanine and cysteine mainly in glial cells and neurons.^60,61 In addition, it has been verified that mutations in SLC1A4 are associated with developmental delay, microcephaly and hypomyelination. ⁶² The enrichment analysis of these 53 genes revealed a predominance of biological functions associated with intestinal epithelial cells. Intestinal stem cells can differentiate into two types of intestinal epithelial cells: the absorptive type (enterocytes) and the secretory type (Paneth cells that secrete antimicrobial peptides, goblet cells that produce mucus, and various hormone-secreting enteroendocrine cells). ⁶³ In addition, the gut contains a large number of immune cells (T cells, B cells, dendritic cells, innate lymphocytes, etc.). ⁶⁴ These immune cells impact intestinal epithelial cells by secreting cytokines such as IL-6 from intraepithelial lymphocytes, which promote intestinal epithelial cell proliferation, ⁶⁵ and tumour necrosis factor-α and interferon-γ, which inhibit epithelial cell proliferation by inhibiting β-catenin/T-cell factor signalling. ⁶⁶ Our results of TF network demonstrated that the differential expression of regulatory factors can change the proliferation of intestinal epithelial cells and the intestinal microenvironment.

Conclusions

In conclusion, the effects of esketamine on the intestinal microenvironment and intestinal microbiota were explored using a mouse model and bioinformatics technology. Specifically, esketamine significantly altered the abundance of gut microbiota, such as Adlercreutzia equolifaciens and Akkermansia. Enrichment analysis of DEGs, mRNAs in the ceRNA regulatory network, and target genes in the TF network showed that ketamine could change the intestinal microenvironment, including the immune environment and transport mode. However, the intestinal microenvironment and intestinal flora of mice and humans are different, and the specific relationship and mechanism of esketamine with human intestinal flora and microenvironment requires further clinical studies. The effect of esketamine on human intestinal flora can be investigated by further sampling and analysis of feces of people who have undergone surgery by anesthesia with esketamine injection after permission. And this study provides a foundation for further clinical exploration.