Biogeography of intestinal mucus-associated microbiome: Depletion of genus Pseudomonas is associated with depressive-like behaviors in female cynomolgus macaques.

INTRODUCTION: Depression is a debilitating and poorly understood mental disorder. There is an urgency to explore new potential biological mechanisms of depression and the gut microbiota is a promising research area. OBJECTIVES: Our study was aim to understand regional heterogeneity and potential molecular mechanisms underlying depression induced by dysbiosis of mucus-associated microbiota. METHODS: Here, we only selected female macaques because they are more likely to form a natural social hierarchy in a harem-like environment. Because high-ranking macaques rarely displayed depressive-like behaviors, we selected seven monkeys from high-ranking individuals as control group (HC) and the same number of low-ranking ones as depressive-like group (DL), which displayed significant depressive-like behaviors. Then, we collected mucus from the duodenum, jejunum, ileum, cecum and colon of DL and HC monkeys for shotgun metagenomic sequencing, to profile the biogeography of mucus-associated microbiota along duodenum to colon. RESULTS: Compared with HC, DL macaques displayed noticeable depressive-like behaviors such as longer duration of huddle and sit alone behaviors (negative emotion behaviors), and fewer duration of locomotion, amicable and ingestion activities (positive emotion behaviors). Moreover, the alpha diversity index (Chao) could predict aforementioned depressive-like behaviors along duodenum to colon. Further, we identified that genus Pseudomonas was consistently decreased in DL group throughout the entire intestinal tract except for the jejunum. Specifically, there were 10, 18 and 28 decreased Pseudomonas spp. identified in ileum, cecum and colon, respectively. Moreover, a bacterial module mainly composed of Pseudomonas spp. was positively associated with three positive emotion behaviors. Functionally, Pseudomonaswas mainly involved in microbiota derived lipid metabolisms such as PPAR signaling pathway, cholesterol metabolism, and fat digestion and absorption. CONCLUSION: Different regions of intestinal mucus-associated microbiota revealed that depletion of genus Pseudomonas is associated with depressive-like behaviors in female macaques, which might induce depressive phenotypes through regulating lipid metabolism.

ProMENDA: an updated resource for proteomic and metabolomic characterization in depression.

Depression is a prevalent mental disorder with a complex biological mechanism. Following the rapid development of systems biology technology, a growing number of studies have applied proteomics and metabolomics to explore the molecular profiles of depression. However, a standardized resource facilitating the identification and annotation of the available knowledge from these scattered studies associated with depression is currently lacking. This study presents ProMENDA, an upgraded resource that provides a platform for manual annotation of candidate proteins and metabolites linked to depression. Following the establishment of the protein dataset and the update of the metabolite dataset, the ProMENDA database was developed as a major extension of its initial release. A multi-faceted annotation scheme was employed to provide comprehensive knowledge of the molecules and studies. A new web interface was also developed to improve the user experience. The ProMENDA database now contains 43,366 molecular entries, comprising 20,847 protein entries and 22,519 metabolite entries, which were manually curated from 1370 human, rat, mouse, and non-human primate studies. This represents a significant increase (more than 7-fold) in molecular entries compared to the initial release. To demonstrate the usage of ProMENDA, a case study identifying consistently reported proteins and metabolites in the brains of animal models of depression was presented. Overall, ProMENDA is a comprehensive resource that offers a panoramic view of proteomic and metabolomic knowledge in depression. ProMENDA is freely available at https://menda.cqmu.edu.cn .

Gut microbial CAZymes markers for depression.

Major depressive disorder (MDD) is a serious mental illness, characterized by disturbances of gut microbiome, it is required to further explore how the carbohydrate-active enzymes (CAZymes) were changed in MDD. Here, using the metagenomic data from patients with MDD (n = 118) and heath controls (HC, n = 118), we found that the whole CAZymes signatures of MDD were significantly discriminated from that in HC. α-diversity indexes of the two groups were also significantly different. The patients with MDD were characterized by enriched Glycoside Hydrolases (GHs) and Polysaccharide Lyases (PLs) relative to HC. A panel of makers composed of 9 CAZymes mainly belonging to GHs enabled to discriminate the patients with MDD and HC with AUC of 0.824. In addition, this marker panel could classify blinded test samples from the two groups with an AUC of 0.736. Moreover, we found that baseline 4 CAZymes levels also could predict the antidepressant efficacy after adjusted confounding factors and times of depressive episode. Our findings showed that MDD was associated with disturbances of gut CAZymes, which may help to develop diagnostic and predictive tools for depression.

Integrating spatial and single-nucleus transcriptomic data elucidates microglial-specific responses in female cynomolgus macaques with depressive-like behaviors.

Major depressive disorder represents a serious public health challenge worldwide; however, the underlying cellular and molecular mechanisms are mostly unknown. Here, we profile the dorsolateral prefrontal cortex of female cynomolgus macaques with social stress-associated depressive-like behaviors using single-nucleus RNA-sequencing and spatial transcriptomics. We find gene expression changes associated with depressive-like behaviors mostly in microglia, and we report a pro-inflammatory microglia subpopulation enriched in the depressive-like condition. Single-nucleus RNA-sequencing data result in the identification of six enriched gene modules associated with depressive-like behaviors, and these modules are further resolved by spatial transcriptomics. Gene modules associated with huddle and sit alone behaviors are expressed in neurons and oligodendrocytes of the superficial cortical layer, while gene modules associated with locomotion and amicable behaviors are enriched in microglia and astrocytes in mid-to-deep cortical layers. The depressive-like behavior associated microglia subpopulation is enriched in deep cortical layers. In summary, our findings show cell-type and cortical layer-specific gene expression changes and identify one microglia subpopulation associated with depressive-like behaviors in female non-human primates.

LRFN5 and OLFM4 as novel potential biomarkers for major depressive disorder: a pilot study.

Evidences have shown that both LRFN5 and OLFM4 can regulate neural development and synaptic function. Recent genome-wide association studies on major depressive disorder (MDD) have implicated LRFN5 and OLFM4, but their expressions and roles in MDD are still completely unclear. Here, we examined serum concentrations of LRFN5 and OLFM4 in 99 drug-naive MDD patients, 90 drug-treatment MDD patients, and 81 healthy controls (HCs) using ELISA methods. The results showed that both LRFN5 and OLFM4 levels were considerably higher in MDD patients compared to HCs, and were significantly lower in drug-treatment MDD patients than in drug-naive MDD patients. However, there were no significant differences between MDD patients who received a single antidepressant and a combination of antidepressants. Pearson correlation analysis showed that they were associated with the clinical data, including Hamilton Depression Scale score, age, duration of illness, fasting blood glucose, serum lipids, and hepatic, renal, or thyroid function. Moreover, these two molecules both yielded fairly excellent diagnostic performance in diagnosing MDD. In addition, a combination of LRFN5 and OLFM4 demonstrated a better diagnostic effectiveness, with an area under curve of 0.974 in the training set and 0.975 in the testing set. Taken together, our data suggest that LRFN5 and OLFM4 may be implicated in the pathophysiology of MDD and the combination of LRFN5 and OLFM4 may offer a diagnostic biomarker panel for MDD.

Changes of gut microbiota reflect the severity of major depressive disorder: a cross sectional study.

Disturbed gut microbiota is a potential factor in the pathogenesis of major depressive disorder (MDD), yet whether gut microbiota dysbiosis is associated with the severity of MDD remains unclear. Here, we performed shotgun metagenomic profiling of cross-sectional stool samples from MDD (n = 138) and healthy controls (n = 155). The patients with MDD were divided into three groups according to Hamilton Depression Rating Scale 17 (HAMD-17), including mild (n = 24), moderate (n = 72) and severe (n = 42) individuals, respectively. We found that microbial diversity was closely related to the severity of MDD. Compared to HCs, the abundance of Bacteroides was significantly increased in both moderate and severe MDD, while Ruminococcus and Eubacterium depleted mainly in severe group. In addition, we identified 99 bacteria species specific to severity of depression. Furthermore, a panel of microbiota marker comprising of 37 bacteria species enabled to effectively distinguish MDD patients with different severity. Together, we identified different perturbation patterns of gut microbiota in mild-to-severe depression, and identified potential diagnostic and therapeutic targets.

Gut microbiota and its metabolites in depression: from pathogenesis to treatment.

Major depressive disorder is one of the most disabling mental disorders worldwide. Increasing preclinical and clinical studies have highlighted that compositional and functional (e.g., metabolite) changes in gut microbiota, known as dysbiosis, are associated with the onset and progression of depression via regulating the gut-brain axis. However, the gut microbiota and their metabolites present a double-edged sword in depression. Dysbiosis is involved in the pathogenesis of depression while, at the same time, offering a novel therapeutic target. In this review, we describe the association between dysbiosis and depression, drug-microbiota interactions in antidepressant treatment, and the potential health benefits of microbial-targeted therapeutics in depression, including dietary interventions, fecal microbiota transplantation, probiotics, prebiotics, synbiotics, and postbiotics. With the emergence of microbial research, we describe a new direction for future research and clinical treatment of depression.

The gut microbiome modulates the transformation of microglial subtypes.

Clinical and animal studies have shown that gut microbiome disturbances can affect neural function and behaviors via the microbiota-gut-brain axis, and may be implicated in the pathogenesis of several brain diseases. However, exactly how the gut microbiome modulates nervous system activity remains obscure. Here, using a single-cell nucleus sequencing approach, we sought to characterize the cell type-specific transcriptomic changes in the prefrontal cortex and hippocampus derived from germ-free (GF), specific pathogen free, and colonized-GF mice. We found that the absence of gut microbiota resulted in cell-specific transcriptomic changes. Furthermore, microglia transcriptomes were preferentially influenced, which could be effectively reversed by microbial colonization. Significantly, the gut microbiome modulated the mutual transformation of microglial subpopulations in the two regions. Cross-species analysis showed that the transcriptome changes of these microglial subpopulations were mainly associated with Alzheimer's disease (AD) and major depressive disorder (MDD), which were further supported by animal behavioral tests. Our findings demonstrate that gut microbiota mainly modulate the mutual transformation of microglial subtypes, which may lead to new insights into the pathogenesis of AD and MDD.

Lipid Alteration Signature in the Blood Plasma of Individuals With Schizophrenia, Depression, and Bipolar Disorder.

Importance: No clinically applicable diagnostic test exists for severe mental disorders. Lipids harbor potential as disease markers. Objective: To define a reproducible profile of lipid alterations in the blood plasma of patients with schizophrenia (SCZ) independent of demographic and environmental variables and to investigate its specificity in association with other psychiatric disorders, ie, major depressive disorder (MDD) and bipolar disorder (BPD). Design, Setting, and Participants: This was a multicohort case-control diagnostic analysis involving plasma samples from psychiatric patients and control individuals collected between July 17, 2009, and May 18, 2018. Study participants were recruited as consecutive and volunteer samples at multiple inpatient and outpatient mental health hospitals in Western Europe (Germany and Austria [DE-AT]), China (CN), and Russia (RU). Individuals with DSM-IV or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses of SCZ, MDD, BPD, or a first psychotic episode, as well as age- and sex-matched healthy controls without a mental health-related diagnosis were included in the study. Samples and data were analyzed from January 2018 to September 2020. Main Outcomes and Measures: Plasma lipidome composition was assessed using liquid chromatography coupled with untargeted mass spectrometry. Results: Blood lipid levels were assessed in 980 individuals (mean [SD] age, 36 [13] years; 510 male individuals [52%]) diagnosed with SCZ, BPD, MDD, or those with a first psychotic episode and in 572 controls (mean [SD] age, 34 [13] years; 323 male individuals [56%]). A total of 77 lipids were found to be significantly altered between those with SCZ (n = 436) and controls (n = 478) in all 3 sample cohorts. Alterations were consistent between cohorts (CN and RU: [Pearson correlation] r = 0.75; DE-AT and CN: r = 0.78; DE-AT and RU: r = 0.82; P < 10-38). A lipid-based predictive model separated patients with SCZ from controls with high diagnostic ability (area under the receiver operating characteristic curve = 0.86-0.95). Lipidome alterations in BPD and MDD, assessed in 184 and 256 individuals, respectively, were found to be similar to those of SCZ (BPD: r = 0.89; MDD: r = 0.92; P < 10-79). Assessment of detected alterations in individuals with a first psychotic episode, as well as patients with SCZ not receiving medication, demonstrated only limited association with medication restricted to particular lipids. Conclusions and Relevance: In this study, SCZ was accompanied by a reproducible profile of plasma lipidome alterations, not associated with symptom severity, medication, and demographic and environmental variables, and largely shared with BPD and MDD. This lipid alteration signature may represent a trait marker of severe psychiatric disorders, indicating its potential to be transformed into a clinically applicable testing procedure.

Fusobacterium nucleatum promotes proliferation in oesophageal squamous cell carcinoma via AHR/CYP1A1 signalling.

Fusobacterium nucleatum (Fn) is reportedly involved in poor prognosis of oesophageal squamous cell carcinoma (ESCC), but the responsible mechanisms remain unclear. The present study aimed to explore the function of Fn in ESCC progression, and to identify the key genes or signals involved. Fluorescence in situ hybridization and quantitative PCR assays were applied to measure the abundance of Fn in ESCC tissues, finding that ESCC tissues displayed a higher abundance of Fn compared to adjacent tissues. Furthermore, Fn abundance in advanced ESCC tissues was found to be higher than that in early stage ESCC. The proliferation assays and wound healing assays indicated that Fn infection promoted ESCC cell proliferation and migration. Based on high-throughput sequencing, cytochrome P450 1A1 (CYP1A1) was the most significantly upregulated (eightfold increase) gene, and AKT signalling was activated in KYSE-450 cells treated with Fn. Knocking down CYP1A1 or inactivating AKT signalling with LY294002 downregulated p-AKTS473 , inhibited cell proliferation, and compromised the proliferation effect induced by Fn in both in vitro and in vivo experiments. Inactivating the aryl hydrocarbon receptor (AHR) by CH-223191 reversed CYP1A1 expression induced by Fn and inhibited the proliferation of ESCC cells. Taken together, our findings indicate that Fn may promote ESCC cell proliferation via AHR/CYP1A1/AKT signalling. Targeting Fn or AHR/CYP1A1 signalling could yield approaches relevant to the treatment of ESCC.

Altered neurometabolite levels in the brains of patients with depression: A systematic analysis of magnetic resonance spectroscopy studies.

BACKGROUND: Numerous magnetic resonance spectroscopy (MRS) studies have reported metabolic abnormalities in the brains of patients with depression, although inconsistent results have been reported. The aim of this study was to explore changes in neurometabolite levels in patients with depression across large-scale MRS studies. METHOD: A total of 307 differential metabolite entries associated with depression were retrieved from 180 MRS studies retrieved from the Metabolite Network of Depression Database. The vote-counting method was used to identify consistently altered metabolites in the whole brain and specific brain regions of patients with depression. RESULTS: Only few differential neurometabolites showed a stable change trend. The levels of total choline (tCho) and the tCho/N-acetyl aspartate (NAA) ratio were consistently higher in the brains of patients with depression, and that the levels of NAA, glutamate and glutamine (Glx), and gamma-aminobutyric acid (GABA) were lower. For specific brain regions, we found lower Glx levels in the prefrontal cortex and lower GABA concentrations in the occipital cortex. We also found lower concentrations of NAA in the anterior cingulate cortex and prefrontal cortex. The levels of tCho were higher in the prefrontal cortex and putamen. CONCLUSION: Our results revealed that most altered neurometabolites in previous studies lack of adequate reproducibility. Through vote-counting method with large-scale studies, downregulation of glutamatergic neurometabolites, impaired neuronal integrity, and disturbed membrane metabolism were found in the pathobiology of depression, which contribute to existing knowledge of neurometabolic changes in depression. Further studies based on a larger dataset are needed to confirm our findings.

Toward a Deeper Understanding of Gut Microbiome in Depression: The Promise of Clinical Applicability.

The emergence of the coronavirus disease 2019 pandemic has dramatically increased the global prevalence of depression. Unfortunately, antidepressant drugs benefit only a small minority of patients. Thus, there is an urgent need to develop new interventions. Accumulating evidence supports a causal relationship between gut microbiota dysbiosis and depression. To advance microbiota-based diagnostics and therapeutics of depression, a comprehensive overview of microbial alterations in depression is presented to identify effector microbial biomarkers. This procedure generated 215 bacterial taxa from humans and 312 from animal models. Compared to controls, depression shows significant differences in ß-diversity, but no changes in microbial richness and diversity. Additionally, species-specific microbial changes are identified like increased Eggerthella in humans and decreased Acetatifactor in rodent models. Moreover, a disrupted microbiome balance and functional changes, characterized by an enrichment of pro-inflammatory bacteria (e.g., Desulfovibrio and Escherichia/Shigella) and depletion of anti-inflammatory butyrate-producing bacteria (e.g., Bifidobacterium and Faecalibacterium) are consistently shared across species. Confounding effects of geographical region, depression type, and intestinal segments are also investigated. Ultimately, a total of 178 species and subspecies probiotics are identified to alleviate the depressive phenotypes. Current findings provide a foundation for developing microbiota-based diagnostics and therapeutics and advancing microbiota-oriented precision medicine for depression.

Self-Assembled Networks for Regulating Lithium Polysulfides in Lithium-Sulfur Batteries.

Inhibiting the shuttle effect caused by soluble lithium polysulfides (LiPSs) is of importance for lithium-sulfur (Li-S) batteries. Here, a strategy was developed to construct protective layers by self-assembly networks to regulate the LiPSs. 2,5-Dichloropyridine (25DCP) holds two kinds of functional groups. Among them, the two C-Cl bonds were nucleophilic substituted by S in LiPSs to form long chains. The pyridine N interacted with Li in other LiPSs via Li bonds to form a short chain. As a result, the long chains were cross-linked by the short chain to form an insoluble network. The as-prepared network covered the sulfur electrode interface to suppress the shuttle effect of the subsequently generated LiPSs. Furthermore, 25DCP improved the redox dynamics by changing the energy level and electronic structure of the sulfur species. Therefore, the Li-S batteries with 25DCP exhibited good electrochemical performance. This work provides a feasible strategy for regulating the LiPSs.

Perturbed gut microbiota is gender-segregated in unipolar and bipolar depression.

OBJECTIVE: This study aimed to explore the gender specificity of gut microbiome in patients with unipolar and bipolar depression disorder by analyzing the data of gut microbiome in this two mental disorders and healthy people. METHODS: A case-control study using 16S ribosomal RNA gene sequencing from fecal samples of MDD (male set, n = 43; female set, n = 77) and BD (male set, n = 82; female set, n = 83) compared with HCs (male set, n = 71; female set, n = 100) was conducted. Linear discriminant analysis was used to identify microbial characteristics. Through cooccurrence analysis, the potential correlations of the differential gut microbiota in different genders was explored. Finally, the gender-specific distinguishing microorganisms were identified as biomaker, and the diagnostic performance was verified by five-fold cross validation. RESULTS: A specific cluster was found enriched only in female MDD set, including 4 Bacteroideae OTUs. Similarly, 3 Lachnospiraceae OTUs was found significantly increased in female BD compared with other groups. In addition, the consistent enrichment of Pseudomonadacea in male and female may be the characteristic disease-related gut microbiota of BD. Besides, the diagnostic potential of gender specific biomarker panel in male (male validation AUC: 0.758-0.874, accurancy: 0.693-0.792; female validation AUC: 0.727-0.883, accurancy: 0.678-0.781) and female (male validation AUC: 0.787-0.883, accurancy: 0.719-0.784; female validation AUC: 0.795-0.898, accurancy: 0.689-0.838) has also been identified and confirmed. CONCLUSIONS: The microbiological changes in both MDD and BD are sex specific, and gender specific biomarker panel has better diagnostic performance, which provide a certain reference in sex difference for future clinical differentiation and microbial intervention.

Altered Metabolism of the Microbiota-Gut-Brain Axis Is Linked With Comorbid Anxiety in Fecal Recipient Mice of Myasthenia Gravis.

Myasthenia gravis (MG) comorbid anxiety seriously affects the progress of MG. However, the exact relationship remains poorly understood. Recently, our preliminary study has revealed that intestinal microbe disturbance is closely related to MG. Therefore, further exploration of whether the microbiome is involved in MG comorbid anxiety is warranted. In this study, gas chromatography-mass spectrometry metabolomics analysis was used to characterize the metabotype of feces, serum, and three brain regions involved in emotion (i.e., the prefrontal cortex, hippocampus, and striatum), which were obtained from mice that were colonized with fecal microbiota from patients with MG (MMb), healthy individuals (HMb), or co-colonization of both patients and healthy individuals (CMb). Functional enrichment analysis was used to explore the correlation between the "microbiota-gut-brain" (MGB) axis and anxiety-like behavior. The behavioral test showed that female MMb exhibited anxiety-like behavior, which could be reversed by co-colonization. Moreover, metabolic characterization analysis of the MGB axis showed that the metabotype of gut-brain communication was significantly different between MMb and HMb, and 146 differential metabolites were jointly identified. Among these, 44 metabolites in feces; 12 metabolites in serum; 7 metabolites in hippocampus; 2 metabolites in prefrontal cortex; and 6 metabolites in striatum were reversed by co-colonization. Furthermore, the reversed gut microbiota mainly belonged to bacteroides and firmicutes, which were highly correlated with the reversed metabolites within the MGB axis. Among three emotional brain regions, hippocampus was more affected. Therefore, disturbances in gut microbiota may be involved in the progress of anxiety-like behavior in MG due to the MGB axis.

Changes in gut viral and bacterial species correlate with altered 1,2-diacylglyceride levels and structure in the prefrontal cortex in a depression-like non-human primate model.

Major depressive disorder (MDD) is a debilitating mental disease, but its underlying molecular mechanisms remain obscure. Our previously established model of naturally occurring depression-like (DL) behaviors in Macaca fascicularis, which is characterized by microbiota-gut-brain (MGB) axis disturbances, can be used to interrogate how a disturbed gut ecosystem may impact the molecular pathology of MDD. Here, gut metagenomics were used to characterize how gut virus and bacterial species, and associated metabolites, change in depression-like monkey model. We identified a panel of 33 gut virus and 14 bacterial species that could discriminate the depression-like from control macaques. In addition, using lipidomic analyses of central and peripheral samples obtained from these animals, we found that the DL macaque were characterized by alterations in the relative abundance, carbon-chain length, and unsaturation degree of 1,2-diacylglyceride (DG) in the prefrontal cortex (PFC), in a brain region-specific manner. In addition, lipid-reaction analysis identified more active and inactive lipid pathways in PFC than in amygdala or hippocampus, with DG being a key nodal player in these lipid pathways. Significantly, co-occurrence network analysis showed that the DG levels may be relevant to the onset of negative emotions behaviors in PFC. Together our findings suggest that altered DG levels and structure in the PFC are hallmarks of the DL macaque, thus providing a new framework for understanding the gut microbiome's role in depression.

Metabolomic changes in animal models of depression: a systematic analysis.

Extensive research has been carried out on the metabolomic changes in animal models of depression; however, there is no general agreement about which metabolites exhibit constant changes. Therefore, the aim of this study was to identify consistently altered metabolites in large-scale metabolomics studies of depression models. We performed vote counting analyses to identify consistently upregulated or downregulated metabolites in the brain, blood, and urine of animal models of depression based on 3743 differential metabolites from 241 animal metabolomics studies. We found that serotonin, dopamine, gamma-aminobutyric acid, norepinephrine, N-acetyl-L-aspartic acid, anandamide, and tryptophan were downregulated in the brain, while kynurenine, myo-inositol, hydroxykynurenine, and the kynurenine to tryptophan ratio were upregulated. Regarding blood metabolites, tryptophan, leucine, tyrosine, valine, trimethylamine N-oxide, proline, oleamide, pyruvic acid, and serotonin were downregulated, while N-acetyl glycoprotein, corticosterone, and glutamine were upregulated. Moreover, citric acid, oxoglutaric acid, proline, tryptophan, creatine, betaine, L-dopa, palmitic acid, and pimelic acid were downregulated, and hippuric acid was upregulated in urine. We also identified consistently altered metabolites in the hippocampus, prefrontal cortex, serum, and plasma. These findings suggested that metabolomic changes in depression models are characterized by decreased neurotransmitter and increased kynurenine metabolite levels in the brain, decreased amino acid and increased corticosterone levels in blood, and imbalanced energy metabolism and microbial metabolites in urine. This study contributes to existing knowledge of metabolomic changes in depression and revealed that the reproducibility of candidate metabolites was inadequate in previous studies.

Dynamic changes occur in the DNA gut virome of female cynomolgus macaques during aging.

Aging is a critical factor affecting physical health and disease in mammals. Emerging evidence indicates that aging may affect the gut bacteriome in cynomolgus macaques, but little is known about whether or how the gut virome changes with age. Here, we compared the DNA gut viral composition of 16 female cynomolgus monkeys (Macaca fascicularis) at three life stages (young, adult, and old) using the shotgun metagenome sequencing method. We found that the DNA gut virome from these monkeys differed substantially among the three groups. The gut viruses were dominated by bacteriophages, the most abundant of which was the Caudovirales order (i.e., Siphoviridae, Myoviridae, and Podoviridae families). Additionally, the co-occurrence analysis revealed that the age-related bacteriophages were correlated in an extensive and complex manner with the main intestinal bacteria (i.e., Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria phyla). Furthermore, the age-related DNA gut viral functions were enriched for genetic information processing, nucleotide, and folate metabolism. Our gut virome analysis provides new insight into how aging influences the gut virome of non-human primates.

Characterization of gut microbiome in mice model of depression with divergent response to escitalopram treatment.

Depression is a common and heterogeneous mental disorder. Although several antidepressants are available to treat the patients with depression, the factors which could affect and predict the treatment response remain unclear. Here, we characterize the longitudinal changes of microbial composition and function during escitalopram treatment in chronic unpredictable mild stress (CUMS) mice model of depression based on 16 S rRNA sequencing and metabolomics. Consequently, we found that escitalopram (ESC) administration serves to increase the alpha-diversity of the gut microbiome in ESC treatment group. The microbial signatures between responder (R) and non-responder (NR) groups were significantly different. The R group was mainly characterized by increased relative abundances of genus Prevotellaceae_UCG-003, and depleted families Ruminococcaceae and Lactobacillaceae relative to NR group. Moreover, we identified 15 serum metabolites responsible for discriminating R and NR group. Those differential metabolites were mainly involved in phospholipid metabolism. Significantly, the bacterial OTUs belonging to family Lachnospiraceae, Helicobacteraceae, and Muribaculaceae formed strong co-occurring relationships with serum metabolites, indicating alternations of gut microbiome and metabolites as potential mediators in efficiency of ESC treatment. Together, our study demonstrated that the alterations of microbial compositions and metabolic functions might be relevant to the different response to ESC, which shed new light in uncovering the mechanisms of differences in efficacy of antidepressants.