Characterization Of Metabolome And Intestinal Flora In Depressive Patients And Mechanism Study On The Antidepressive Effects Of Bacopaside ?

Major depressive disorder(MDD)is a chronic mental disorder characterized by low mood,lack of interest,slow thinking,sense of worthless and guilt.It is often accompanied by symptoms such as loss of appetite,increase of fatigue,insomnia and inattention,and characterized by high prevalence,high mortality,high recurrence rate and high suicide rate.The pathogenesis of depression is very complicated,and generally considered to be related to many factors such as heredity,biochemistry,endocrinology,immunity,social psychology,culture and so on.At present,the clinical diagnosis of depression mainly depends on the doctor's judgment on the symptoms of the patient by using scales.However,this diagnostic method is influenced by the experience of the clinician and the subjective factors of the patient,which leads to inaccurate and ineffective diagnosis of depression.Therefore,our efforts to discover potential biomarkers related to depression through metabolomics can not only help reveal its pathological mechanism,but also provide an important material basis for the early diagnosis and prognosis of depression.In addition,in recent years,it has been found that the intestinal flora is closely related to the occurrence and development of depression,and the intestinal flora affects the host's metabolic phenotype and participates in the host's co-metabolism process.This co-metabolism relationship plays a significant role in maintaining the host's physiological health.However,most studies on the relationship between depression and intestinal flora are based on animal models.Therefore,we investigated how the structural changes of intestinal flora in depressive patients affect their metabolic phenotypes,thus revealing the pathophysiological mechanisms how the intestinal flora is involved in the overall metabolism of depression.On the other hand,the certain degree of side effects,low effective cure rate and patients' significant individual differences in antidepressants lead to poor clinical treatment.So it has become a research hotspot to find effective antidepressant drugs with less side effects.In this paper,based on UPLC-Q/TOF-MS technology,metabonomic researches were carried out to study metablome of the serum and urine from a group of clinically recruited patients with depression to screen potential biomarkers related to depression.And then the Illumina MiSeq high-throughput sequencing and multivariate statistical methods were used to comprehensively analyze the V3-V4 region of16 S rDNA gene of fecal bacteria of the depressive patients,and to explore the overall structural diversity of intestinal flora in depressive patients and identify disease-related bacterial species.On the basis of this study,the possible effects of changes in intestinalflora on metabolic phenotypes of depression were studied.In addition,based on the natural product activity screening platform of our research group,we filtrated one saponin compound,Bacopaside ?,which exhibibited potent antidepressant activity.Then we explored its antidepressant mechanism by combining metabonomics and molecular biology.The experiments are as follows in detail:1.The serum and urine samples of a group of clinically recruited depressive patients and healthy controls were studied by means of UPLC-Q/TOF-MS technique.The research results show that the orthogonal partial least squares discriminant analysis(OPLS-DA)multivariate statistical score plot displayed on serum and urine samples of patients with depression and healthy controls exist obvious trend of classification,combined with the statistical analysis method of single variables,50 serum differential metabolites and 75 urine differential metabolites related to depression were screened out.Based on the enrichment analysis of the metabolic pathways involved in these differential metabolites by means of MetaboAnalyst software,we found that the abnormalities of serum metabolites in patients with depression are mainly manifested in glycerophospholipid metabolism,bile acid biosynthesis and sphingolipid metabolism,while the differential metabolites in urine mainly involve arginine and proline metabolism,caffeine metabolism,D-arginine and D-ornithine metabolism,purine metabolism,aminoacyl-tRNA biosynthesis and lysine biosynthesis and so on.In addition,based on the binary logistic regression model,12 serum metabolites with AUC greater than 0.9 were screened and the ROC curve of 4 carnitine metabolites as biomarkers was drawn,which showed that the area under the ROC curve was 0.991,the sensitivity was 96.5%,and the specificity was 93%.Similarly,we screened four urine metabolites with AUC greater than 0.8 as biomarkers to construct the ROC curve in which the area was 0.897,sensitivity 86% and specificity 84.2%.The above studies lay a foundation for further understanding of the pathogenesis of depression and early screening and diagnosis of depression in clinical.2.Next,the Illumina MiSeq high-throughput sequencing was used to fully analyze the diversity of intestinal flora in patients with depression and healthy people.Although there were significant individual differences in fecal flora between the two groups,there was no significant difference in the diversity and richness of intestinal flora between the depressive patients and the control group.The dominant phylum was Firmicutes,Bacteroides and Proteobacteria,and the abundance ratio of Firmicutes to Bacteroides in depressive patients significantly increased.Beta diversity analysis revealed that there weresignificant differences in the intestinal flora structure between depressive patients and healthy people.Further studies showed that the main feature of the intestinal flora structure imbalance was significant increase in the abundance of some pathogenic bacteria or potential pathogenic bacteria,while the abundance of butyrate-producing and anti-inflammatory bacteria beneficial to the gut was significantly reduced.These changes in flora may play a role in the development of depression.This study enriched the etiology of depression from the perspective of intestinal microecology and laid a foundation for the prevention and treatment of depression by optimizing the structure of intestinal flora as the therapeutic target in the future.3.On the basis of the previous 1-2 studies,Pearson correlation coefficient was used to calculate the correlation between the differential metabolites screened from serum and urine and the intestinal flora data obtained from high-throughput sequencing of 16 S rDNA gene.It was found that the bacteria-producing SCFA in the intestine of the depressive patients has a correlation with metabolites involved in energy metabolism,bile acid metabolism and neurotransmitter metabolism of amino acids.This suggested that the imbalance of intestinal flora structure may affect these metabolic pathways,thereby affecting the host metabolic phenotype,which provides a reference for further exploration of the pathophysiological mechanism of intestinal flora involved in the overall metabolism of patients with depression.4.The antidepressant effect of Bacopaside ? was evaluated on the internationally recognized CUMS induced depression mice model.The results showed that Bacopaside ? could significantly increase sucrose solution intake of CUMS mice and reduce the immobility time of mice in tail suspension and forced swimming,with no effect on the excitability of the center.This suggested that Bacopaside ? could improve the depressive behavior in CUMS mice.The experimental results of ELISA,RT-qPCR and Western blot showed that Bacopaside ? could significantly decrease the plasma corticosterone content in CUMS mice,increase the expressions of GR and BDNF mRNA in the hippocampus and prefrontal cortex of CUMS mice and increase the expression of GR,BDNF,pERK and pCREB protein in hippocampus and prefrontal cortex.These suggested that the antidepressant mechanism of Bacopaside ? might be mediated by regulating the hyperactivity of the HPA axis and activating the BDNF signal pathway in the hippocampus and the prefrontal tissue.In addition,the metabonomic studies were carried out on plasma samples of the micewith high Bacopaside ? dose based on UPLC-Q/TOF-MS technology in order to further explore the influence of Bacopaside ? on the overall metabolic profiles of depressive mice and relevant mechanism.The results showed that there were significant differences in plasma profiles of mice in model group and control group and that of mice in drug intervention group and model group.Combined with multivariate statistical method,we identified 35 differential metabolites associated with the CUMS model.As compared with the model group,16 endogenous metabolites were significantly changed.In fluoxetine group,25 endogenous metabolites were significantly changed,compared with the model group.And Bacopaside ? and fluoxetine simultaneously regulate 15 An endogenous metabolite.Further analysis revealed that CUMS-induced depression mice were dysregulated in glycerophospholipid metabolism,sphingolipid metabolism,alpha-linolenic acid metabolism,linoleic acid metabolism,amino acid metabolism,and oxidative stress.The antidepressant effect of Fluoxetine and Bacopaside ? may be by regulating the metabolic pathways of these disorders.In summary,endogenous differential metabolites related to in the serum and urine were screened by using UPLC-Q/TOF-MS technology.Moreover,the abnormal metabolic pathways associated with the pathogenesis of depression were also analyzed to reveal the related pathological mechanism of depression at the overall level.Then the Illumina MiSeq high-throughput sequencing was used to fully analyze the overall diversity of intestinal flora in patients with depression and identify disease-related bacterial species.And based on this research,the possible effects of changes in intestinal flora on metabolic phenotypes of depression were studied,thus revealing the pathophysiological mechanism of intestinal flora involved in the overall metabolism of depression,which has great significance for the future diagnosis and treatment of depression.In addition,the natural product Bacopaside ? was screened out through our natural product screening platform.We used molecular biology and metabonomics technology to study the antidepressant mechanism of Bacopaside ?,and elucidated the related pathways and mechanisms of its treatment for depression.These work provide new ideas for the further search for novel and effective antidepressants.