Explore The Relationship Between The Major Depressive Disorder And The Gut Microbiota By 16s RRNA Sequences Analysis

BackgroundMajor depressive disorder(MDD) is a complex mental disorder of the interaction between genes and environment, a serious threat to human health; its prevalence rate of 15% and accounting for 12.3% of the global burden of disease. The World Health Organization predicts that by 2020, MDD will become the second largest health-threatening disease. Therefore, it is urgent to strengthen the research on the prevention, treatment and pathogenesis of depression. The theory of the pathogenesis of MDD is numerous, mainly focusing on the brain molecular abnormalities theory, including lack of neurotransmission, neural nutrition disorders, and the abnormity of neuroendocrine system, immunologic system and neuroanatomy. These abnormal theories of brain provide some theoretical basis for revealing the cause of depression, but most of them can only explain some aspects. For example, clinical based on brain monoamine neurotransmitter imbalance theory and development of antidepressant treatment can only relieve the symptoms in 40% of patients. Therefore, although the incidence of depression in the brain is an important factor, but the external environment factors and its mechanism of action is more urgent to clarify.Microorganisms in the gut is 10-fold greater than the number of human cells. These microorganisms also contain 150-fold more genes than the human genome. Therefore, gut microbiota are considered to be the largest and most direct external environment, which plays an important role in the maintenance of human health. Recent studies suggest that gut microbiota can affect the biochemical and behavioral phenotype of the brain via the gut brain axis. A study on the metabolism of MDD in the previous period of our task group reports that metabolic disorder(for example, hippurate, two methylamine and two methyl glycine) of intestinal microbial origin in MDD, suggested that the intestinal microbial disorder may be an important feature of depression.ObjectiveUsing 16 S r RNA gene sequencing, the gut microbial communities of 58 MDD patients and 63 healthy controls were compared to evaluate whether alterations in the gut microbiome are significant in MDD patients and the key to the disorder of intestinal microorganisms and to lay a foundation for further research on the key to the pathogenesis of intestinal microbes and depression.Method1. Study participantsMDD diagnoses were carried out according to the Structured Psychiatric Interview using DSM-IV--TR criteria, and the 17-item Hamilton Depression Rating Scale(HDRS) was used to quantify the severity of MDD. A total of 58 MDD patients and 63 demographically-matched healthy controls were recruited. The majority of MDD subjects(n=39) were drug-na?ve, while the remaining MDD subjects(n=19) were being treated with various anti-depressants.2. Sample collection and extractionFecal samples were collected from the recruited subjects, frozen immediately following collection, and stored at-80°C prior to analyses. Fecal samples were pulverized with a mortar and pestle in liquid nitrogen, and bacterial genomic DNA was extracted by the standard Power Soil Kit protocol.3. 16 S r RNA Gene SequencingRoche 454 sequencing: The V3-V5 regions of the 16 S r RNA gene were PCR-amplified with barcoded universal primers.4. 16 S r RNA Gene Sequencing AnalysisRaw sequences obtained from 454 sequencing were quality filtered using Mothur(Version 1.31.2, http://www.mothur.org/) to obtain unique reads. Sequences of less than 200 bp and greater than 1000 bp as well as sequences containing any primer mismatches, barcode mismatches, ambiguous bases, and homopolymer runs exceeding six bases were excluded.All remaining sequences were assigned to operational taxonomic units(OTUs) with a 97% threshold of pairwise identity and then classified taxonomically using the RDP reference database(http://www.mothur.org/wiki/RDP_reference_files). These taxonomies were used to construct summaries of the taxonomic distributions of OTUs, which can then be applied to calculate the relative abundances of microbiota at different levels. Alpha diversity was calculated by four different parameters(i) Observed species;(ii) Shannon Index;(iii) phylogenetic diversity and(iv) Simpson. Distance matrices(Beta diversity) between samples were generated based on weighted(Bray-Curtis similarity) and non-weighted(unweighted Uni Frac) algorithms and reported according to principal coordinate analysis(PCo A).To perform the Uni Frac analysis, representative sequences for each OTU were aligned using Py NAST, and a phylogenetic tree from this alignment was constructed with Fast Tree. Random Forest algorithm was carried out to identify the key discriminatory OTUs, which assigns an importance score to each OTU by estimating the increase in error caused by removing that OTU from the set of predictors.Results1. A culture-independent, 16 S ribosomal RNA gene-sequence-based approach, was used to compare the gut microbial communities of MDD patients and healthy controls. DNA was extracted from their fecal samples. We obtained a total of 854639 high-quality 16 S r RNA gene sequences(7063±2352 reads/fecal sample), which were subsequently clustered into operational taxonomic units(OTUs) at a 97% similarity level. The majority of these OTUs belonged to only two phyla(Firmicutes and Bacteroidetes; 83.1% ±11.9%)2. Initially, the within-sample(α) phylogenetic diversity analysis showed that there were no significant difference between the two groups; In addition, the unweighted Uni Frac analysis-- which focuses on the degree of microbial phylogenetic similarity(β-diversity)-- was used to determine the degree by which the gut microbiota within MDD subjects differed from those within healthy control. The three-dimensional plots of unweighted Uni Frac analysis showed an obvious difference in the gut microbial community compositions between MDD patients and healthy controls. A similar discrimination between MDD and healthy control group was also observed using weighted Uni Frac analysis. These differences in the gut microbiomes were not significantly related to any key categorical variables(i.e., sex, smoking status, and antidepressant use) nor to any key continuous variables(i.e., age and BMI).3. Apply a Random Forests classifier, a total of 54 OTUs whose relative abundance reliably distinguished MDD and healthy control samples were identified. Of these 54 differential OTUs, a total of 29 OTUs were overrepresented in MDD subjects and assigned to the families of Actinomycineae, Coriobacterineae, Lactobacillaceae, Streptococcaceae, Clostridiales incertae sedis XI(Parvimonas), Eubacteriaceae, Lachnospiraceae(Anaerostipes, Blautia, Dorea, Lachnospiracea incertae sedis), Ruminococcaceae(Clostridium IV), and Erysipelotrichaceae incertae sedis, while a total of 25 OTUs were overrepresented in healthy control subjects and assigned to the families of Bacteroidaceae, Rikenellaceae(Alistipes), Lachnospiraceae(Coprococcus, Clostridium Xl Va, Lachnospiracea incertae sedis, Roseburia, and Faecalibacterium), Acidaminococcaceae(Phascolarctobacterium), Veillonellaceae(Megamonas), and Sutterellaceae. Those discriminative OTUs were mainly assigned to the phyla Firmicutes(45/56, 76.7%), Actinobacteria(5/56, 10.9%), and Bacteroidetes(3/56, 5.3%) at the level of the gateway. Compared to healthy controls, the relative abundances of Actinobacteria were increased in MDD subjects, while those of Bacteroidetes were decreased. Although there were no significant differences in the overall relative abundances of Firmicutes between MDD patients and healthy controls, change of Firmicutes was still one of hallmark in MDD. This is because some members of the Firmicutes OTUs(24/56) were increased in MDD patients, while others were decreased. In sum, we observed that MDD was associated with a disturbance in the gut microbiome characterized by alterations in specific OTUs assigned to the phyla Firmicutes, Actinobacteria, and Bacteroidetes.ConclusionsThe composition of gut microbiota is significantly altered in MDD patients vis-a-vis healthy control individuals. The relative abundance of Actinobacteria was increased in MDD subjects, while that of Bacteroidetes was decreased, as compared to healthy controls. Moreover, we found that Firmicutes was also responsible for discriminating MDD from healthy controls, although we found no significant difference in the overall relative abundance of Firmicutes between the two groups. Our studies uses the high homogeneity clinical biological samples, firstly provide a direct evidence of depression associated with intestinal microbial disorders, lay the foundation for the further study of the role of intestinal microorganisms in the depression in the next step, and provides a new breakthrough point for the analysis of the new mechanism of depression.