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.

The gut microbiome modulates gut-brain axis glycerophospholipid metabolism in a region-specific manner in a nonhuman primate model of depression.

Emerging research demonstrates that microbiota-gut-brain (MGB) axis changes are associated with depression onset, but the mechanisms underlying this observation remain largely unknown. The gut microbiome of nonhuman primates is highly similar to that of humans, and some subordinate monkeys naturally display depressive-like behaviors, making them an ideal model for studying these phenomena. Here, we characterized microbial composition and function, and gut-brain metabolic signatures, in female cynomolgus macaque (Macaca fascicularis) displaying naturally occurring depressive-like behaviors. We found that both microbial and metabolic signatures of depressive-like macaques were significantly different from those of controls. The depressive-like monkeys had characteristic disturbances of the phylum Firmicutes. In addition, the depressive-like macaques were characterized by changes in three microbial and four metabolic weighted gene correlation network analysis (WGCNA) clusters of the MGB axis, which were consistently enriched in fatty acyl, sphingolipid, and glycerophospholipid metabolism. These microbial and metabolic modules were significantly correlated with various depressive-like behaviors, thus reinforcing MGB axis perturbations as potential mediators of depression onset. These differential brain metabolites were mainly mapped into the hippocampal glycerophospholipid metabolism in a region-specific manner. Together, these findings provide new microbial and metabolic frameworks for understanding the MGB axis' role in depression, and suggesting that the gut microbiome may participate in the onset of depressive-like behaviors by modulating peripheral and central glycerophospholipid metabolism.

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.

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.

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.

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.

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.

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.

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.

Differential Gut Microbiota and Fecal Metabolites Related With the Clinical Subtypes of Myasthenia Gravis.

Myasthenia gravis (MG) is a devastating acquired autoimmune disease. Previous studies have observed that disturbances of gut microbiome may attribute to the development of MG through fecal metabolomic signatures in humans. However, whether there were differential gut microbial and fecal metabolomic phenotypes in different subtypes of MG remains unclear. Here, our objective was to explore whether the microbial and metabolic signatures of ocular (OMG) and generalized myasthenia gravis (GMG) were different, and further identify the shared and distinct markers for patients with OMG and GMG. In this study, 16S ribosomal RNA (rRNA) gene sequencing and gas chromatography-mass spectrometry (GC/MS) were performed to capture the microbial and metabolic signatures of OMG and GMG, respectively. Random forest (RF) classifiers was used to identify the discriminative markers for OMG and GMG. Compared with healthy control (HC) group, GMG group, but not OMG group, showed a significant decrease in α-phylogenetic diversity. Both OMG and GMG groups, however, displayed significant gut microbial and metabolic disorders. Totally, we identified 20 OTUs and 9 metabolites specific to OMG group, and 23 OTUs and 7 metabolites specific to GMG group. Moreover, combinatorial biomarkers containing 15 discriminative OTUs and 2 differential metabolites were capable of discriminating OMG and GMG from each other, as well as from HCs, with AUC values ranging from 0.934 to 0.990. In conclusion, different subtypes of MG harbored differential gut microbiota, which generated discriminative fecal metabolism.

Erratum: Perturbed Microbial Ecology in Myasthenia Gravis: Evidence from the Gut Microbiome and Fecal Metabolome.

[This corrects the article DOI: 10.1002/advs.201901441.].

Gut Microbial Signatures Can Discriminate Unipolar from Bipolar Depression.

Discriminating depressive episodes of bipolar disorder (BD) from major depressive disorder (MDD) is a major clinical challenge. Recently, gut microbiome alterations are implicated in these two mood disorders; however, little is known about the shared and distinct microbial characteristics in MDD versus BD. Here, using 16S ribosomal RNA (rRNA) gene sequencing, the microbial compositions of 165 subjects with MDD are compared with 217 BD, and 217 healthy controls (HCs). It is found that the microbial compositions are different between the three groups. Compared to HCs, MDD is characterized by altered covarying operational taxonomic units (OTUs) assigned to the Bacteroidaceae family, and BD shows disturbed covarying OTUs belonging to Lachnospiraceae, Prevotellaceae, and Ruminococcaceae families. Furthermore, a signature of 26 OTUs is identified that can distinguish patients with MDD from those with BD or HCs, with area under the curve (AUC) values ranging from 0.961 to 0.986 in discovery sets, and 0.702 to 0.741 in validation sets. Moreover, 4 of 26 microbial markers correlate with disease severity in MDD or BD. Together, distinct gut microbial compositions are identified in MDD compared to BD and HCs, and a novel marker panel is provided for distinguishing MDD from BD based on gut microbiome signatures.

Landscapes of bacterial and metabolic signatures and their interaction in major depressive disorders.

Gut microbiome disturbances have been implicated in major depressive disorder (MDD). However, little is known about how the gut virome, microbiome, and fecal metabolome change, and how they interact in MDD. Here, using whole-genome shotgun metagenomic and untargeted metabolomic methods, we identified 3 bacteriophages, 47 bacterial species, and 50 fecal metabolites showing notable differences in abundance between MDD patients and healthy controls (HCs). Patients with MDD were mainly characterized by increased abundance of the genus Bacteroides and decreased abundance of the genera Blautia and Eubacterium These multilevel omics alterations generated a characteristic MDD coexpression network. Disturbed microbial genes and fecal metabolites were consistently mapped to amino acid (γ-aminobutyrate, phenylalanine, and tryptophan) metabolism. Furthermore, we identified a combinatorial marker panel that robustly discriminated MDD from HC individuals in both the discovery and validation sets. Our findings provide a deep insight into understanding of the roles of disturbed gut ecosystem in MDD.

Age-related changes in microbial composition and function in cynomolgus macaques.

Age can significantly affect human physiology and disease risk. Recent studies have shown that age may affect the composition and function of the gut microbiota, but the underlying mechanisms remain largely unknown. Non-human primates are an ideal model for uncovering how age shapes the gut microbiota, as their microbial composition is highly similar to that of humans and is not easily affected by confounding factors. Here, using the 16S rRNA and metagenomic sequencing methods, we characterized the microbial phenotypes of 16 female cynomolgus macaques from three age groups (young, adult and old). Our findings revealed significant differences in microbial composition among the three groups. With increased age, the relative abundances of Veillonellaceae, Coriobacteriaceae and Succinivibrionaceae were significantly increased, Ruminococcaceae and Rikenellaceae were significantly decreased at the family level. Functional enrichment showed that genes that differed among the three groups were mainly involved in arginine biosynthesis, purine metabolism and microbial polysaccharides metabolism. Moreover, CAZymes corresponding to polysaccharide degrading activities were also observed among the three groups. In conclusion, we characterized the composition and function of the gut microbiota at different ages, and our findings provide a new entry point for understanding the effects of age on the human body.

Alterations Of Glycerophospholipid And Fatty Acyl Metabolism In Multiple Brain Regions Of Schizophrenia Microbiota Recipient Mice.

BACKGROUND: Schizophrenia is a debilitating psychiatric disorder characterized by molecular and anatomical abnormalities of multiple brain regions. Our recent study showed that dysbiosis of the gut microbiota contributes to the onset of schizophrenia-relevant behaviors, but the underlying mechanisms remain largely unknown. PURPOSE: This study aimed to investigate how gut microbiota shapes metabolic signatures in multiple brain regions of schizophrenia microbiota recipient mice. METHODS: Gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) were used to compare the metabolic signatures in the cortex, cerebellum and striatum of schizophrenia microbiota and healthy microbiota recipient mice. Enrichment analysis was further conducted to uncover the crucial metabolic pathways related to schizophrenia-relevant behaviors. RESULTS: We found that the metabolic phenotypes of these three regions were substantially different in schizophrenia microbiota recipient mice from those in healthy microbiota recipient mice. In total, we identified 499 differential metabolites that could discriminate the two groups in the three brain regions. These differential metabolites were mainly involved in glycerophospholipid and fatty acyl metabolism. Moreover, we found four of fatty acyl metabolites that were consistently altered in the three brain regions. CONCLUSION: Taken together, our study suggests that alterations of glycerophospholipid and fatty acyl metabolism are implicated in the onset of schizophrenia-relevant behaviors, which may provide a new understanding of the etiology of schizophrenia.

Perturbed Microbial Ecology in Myasthenia Gravis: Evidence from the Gut Microbiome and Fecal Metabolome.

Myasthenia gravis (MG) is a devastating acquired autoimmune disease. Emerging evidence indicates that the gut microbiome plays a key role in maintaining immune system homeostasis. This work reports that MG is characterized by decreased α-phylogenetic diversity, and significantly disturbed gut microbiome and fecal metabolome. The altered gut microbial composition is associated with fecal metabolome changes, with 38.75% of altered bacterial operational taxonomic units showing significant correlations with a range of metabolite biomarkers. Some microbes are particularly linked with MG severity. Moreover, a combination of microbial makers and their correlated metabolites enable discriminating MG from healthy controls (HCs) with 100% accuracy. To investigate whether disturbed gut mcirobiome might contribute to the onset of MG, germ-free (GF) mice are initially colonized with MG microbiota (MMb) or healthy microbiota (HMb), and then immunized in a classic mouse model of MG. The MMb mice demonstrate substantially impaired locomotion ability compared with the HMb mice. This effect could be reversed by cocolonizing GF mice with both MMb and HMb. The MMb mice also exhibit similar disturbances of fecal metabolic pathways as found in MG. Together these data demonstrate disturbances in microbiome composition and activity that are likely to be relevant to the pathogenesis of MG.