Shotgun metagenomics reveals both taxonomic and tryptophan pathway differences of gut microbiota in major depressive disorder patients

Faecal microbiota transplantation from patients with depression or healthy individuals into rats modulates mood-related behaviour

Differences in gut microbiota composition have been observed in patients with major depressive disorder (MDD) compared to healthy individuals. Here, we investigated if faecal microbiota transplantation (FMT) from patients with MDD into rats could induce a depressive-like phenotype. We performed FMT from patients with MDD (FMT-MDD) and healthy individuals (FMT-Healthy) into male Flinders Sensitive Line (FSL) and Flinders Resistant Line (FRL) rats and assessed depressive-like behaviour. No behavioural differences were observed in the FSL rats. In FRL rats, the FMT-Healthy group displayed significantly less depressive-like behaviour than the FMT-MDD group. However, there was no difference in behaviour between FMT-MDD FRL rats and negative controls, indicating that FMT-Healthy FRL rats received beneficial bacteria. We additionally found different taxa between the FMT-MDD and the FMT-Healthy FRL rats, which could be traced to the donors. Four taxa, three belonging to the family Ruminococcaceae and the genus Lachnospira, were significantly elevated in relative abundance in FMT-MDD rats, while the genus Coprococcus was depleted. In this study, the FMT-MDD group was different from the FMT-Healthy group based on behaviour and intestinal taxa.

Characteristics of the lung microbiota in lower respiratory tract infections with and without history of pneumonia

Lung microbiota plays an important role in many diseases including lower respiratory tract infections (LRTI) and pneumonia. This study aimed to explore the effects of community-acquired pneumonia (CAP) on microbial diversity and identify potential biomarkers of respiratory tract in CAP LRTI patients. In the current study, a comprehensive bioinformatics analysis was performed based on metagenomic next generation sequencing technology, followed by alpha and beta diversity, LEfSe, and co-occurrence network analysis, and random forest model construction. Our results showed that CAP dramatically influenced taxon abundance, and the significant differences in microbiota including Proteobacteria, Bacteroidetes, Euryarchaeota, Firmicutes and Spirochaetes were observed at the phylum level. Co-occurrence network selected out novel modules involved in microbial proliferation-associated pathways. A random forest model screened Klebsiella pneumoniae and Bacillus cereus as potential diagnostic biomarkers with high AUC values. The microbial composition was different between CAP LRTI patients and non-CAP LRTI patients. Klebsiella pneumoniae and Bacillus cereus were strongly associated with increased severity of LRTI with a pneumonia history. Our findings provided an insight for a better understanding of community and structure of lung microbiota for future diagnosis and treatment in LRTI patients with a history of pneumonia. Moreover, these microbes were considered as potential biomarkers for predicting the risks for the treatment strategies of LRTI.

Effect of Psychobiotics on Psychometric Tests and Inflammatory Markers in Major Depressive Disorder: Meta-Analysis of Randomized Controlled Trials with Meta-Regression

Probiotics were shown to act positively on gut–brain axis signaling. We aimed to assess the effect of the administration of a new class of probiotics—psychobiotics—using data from individual psychometric scales, markers of the immune system and neuroactive metabolites. Medical databases were searched from database inception until 22 April 2021 for randomized clinical trials in clinically proven Major Depressive Disorder (MDD) patients treated with either probiotics or placebo reporting any psychometric score (PROSPERO registration number: CRD42021253024). Ten studies with 705 randomized participants and 603 analyzed were included. The mean age of individuals was 38.43 ± 12.1 years, predominantly women (n = 461, 76.45). The mean study duration was 48.8 ± 12.3 (range = 28–62) days. The dosage ranged between 1 × 10⁹ to 2 × 10¹⁰ colony forming units (CFU)/day. We found that probiotics might alleviate symptoms of MDD; endpoint data (pooled scores): SMD = −0.292, 95%CI = −0.577 to −0.007, p < 0.044; change scores (BDI): SMD = −0.482, 95%CI = −0.854 to –0.109, p < 0.011; DM = −4.848, 95%CI = −8.559 to −1.137, p < 0.01. The therapy tended to be more effective with time of psychobiotic supplementation (coefficient = −0.12, SE = 0.06, Z = −1.84, p = 0.06) and in men (% of females: coefficient = 0.1, SE = 0.06, Z = 1.78, p = 0.07). Psychobiotics have great potential in the treatment of MDD. However, no specific strain/strains, dosage or duration of treatment can currently be recommended.

Drugs and bugs: Negative affect, psychostimulant use and withdrawal, and the microbiome

BACKGROUND AND OBJECTIVES

A growing body of literature demonstrates that the human microbiota plays a crucial role in health and disease states, as well as in the body's response to stress. In addition, the microbiome plays a role in psychological well-being and regulating negative affect. Regulation of negative affect is a factor in psychostimulant abuse disorders. We propose a risk chain in which stress leads to negative affect that places an individual at risk to develop or relapse to psychostimulant abuse disorder. Stress, negative affect, and psychostimulant use all alter the gut microbiome.

METHODS

This review brings together the literature on affective disorders, stress, and psychostimulant abuse disorders to assess possible modulatory actions of the gut-brain axis to regulate these conditions.

RESULTS

Studies reviewed across the various disciplines suggest that the dysbiosis resulting from drug use, drug withdrawal, or stress may cause an individual to be more susceptible to addiction and relapse. Probiotics and prebiotics reduce stress and negative affect.

SCIENTIFIC SIGNIFICANCE

Treatment during the withdrawal phase of psychostimulant abuse disorder, when the microbiome is altered, may ameliorate the symptoms of stress and negative affect leading to a reduced risk of relapse to psychostimulant use.

Gut Microbiota-Derived Inflammation-Related Serum Metabolites as Potential Biomarkers for Major Depressive Disorder

Background

Although many works have been conducted to explore the biomarkers for diagnosing major depressive disorder (MDD), the widely accepted biomarkers are still not identified. Thus, the combined application of serum metabolomics and fecal microbial communities was used to identify gut microbiota-derived inflammation-related serum metabolites as potential biomarkers for MDD.

Methods

MDD patients and healthy controls (HCs) were included in this study. Both serum samples and fecal samples were collected. The liquid chromatography mass spectrometry (LC-MS) was used to detect the metabolites in serum samples, and the 16S rRNA gene sequencing was used to analyze the gut microbiota compositions in fecal samples.

Results

Totally, 60 MDD patients and 60 HCs were recruited. The 24 differential serum metabolites were identified, and 10 of these were inflammation-related metabolites. Three significantly affected inflammation-related pathways were identified using differential metabolites. The 17 differential genera were identified, and 14 of these genera belonged to phyla Firmicutes. Four significantly affected inflammation-related pathways were identified using differential genera. Five inflammation-related metabolites (LysoPC(16:0), deoxycholic acid, docosahexaenoic acid, taurocholic acid and LysoPC(20:0)) were identified as potential biomarkers. These potential biomarkers had significant correlations with genera belonged to phyla Firmicutes. The panel consisting of these biomarkers could effectively distinguish MDD patients from HCs with an area under the curve (AUC) of 0.95 in training set and 0.92 in testing set.

Conclusion

These findings suggested that the disturbance of phyla Firmicutes might be involved in the onset of depression by regulating host’s inflammatory response, and these potential biomarkers could be useful for future investigating the objective methods for diagnosing MDD.

The change of gut microbiota in MDD patients under SSRIs treatment

The alterations in the gut microbiota have been reported to be correlated with the development of depression. The purpose of this study was to investigate the changes of intestinal microbiota in depressed patients after antidepressant treatment. We recruited 30 MDD patients (MDD group) and 30 healthy controls (control group). The MDD group received individualized treatment with escitalopram at a maximum dose of 20 mg/day. After depressive symptoms improved to a HAMD scale score > 50%, a fecal sample was collected again and used as the follow-up group. The differences of gut microbiota between patients and controls, the characteristics of gut microbiota under treatment and the potential differences in metabolic functions were thus investigated. The Firmicutes/Bacteroidetes ratio was significantly different within three groups, and the ratio of follow-up group was significantly lower than those of the other two groups. Alpha diversity was significantly higher in MDD group than those of the other groups, and the alpha diversity was not significantly different between control and follow-up groups. The beta diversity of some patients resembled participants in the control group. The metabolic function of gut microbiota after treatment was still different from that of the control group. This study suggests that the intestinal flora of depressed patients has a tendency to return to normal under escitalopram treatment.

Bacterial Diversity of Breast Milk in Healthy Spanish Women: Evolution from Birth to Five Years Postpartum

The objective of this work was to characterize the microbiota of breast milk in healthy Spanish mothers and to investigate the effects of lactation time on its diversity. A total of ninety-nine human milk samples were collected from healthy Spanish women and were assessed by means of next-generation sequencing of 16S rRNA amplicons and by qPCR. Firmicutes was the most abundant phylum, followed by Bacteroidetes, Actinobacteria, and Proteobacteria. Accordingly, Streptococcus was the most abundant genus. Lactation time showed a strong influence in milk microbiota, positively correlating with Actinobacteria and Bacteroidetes, while Firmicutes was relatively constant over lactation. 16S rRNA amplicon sequencing showed that the highest alpha-diversity was found in samples of prolonged lactation, along with wider differences between individuals. As for milk nutrients, calcium, magnesium, and selenium levels were potentially associated with Streptococcus and Staphylococcus abundance. Additionally, Proteobacteria was positively correlated with docosahexaenoic acid (DHA) levels in breast milk, and Staphylococcus with conjugated linoleic acid. Conversely, Streptococcus and trans-palmitoleic acid showed a negative association. Other factors such as maternal body mass index or diet also showed an influence on the structure of these microbial communities. Overall, human milk in Spanish mothers appeared to be a complex niche shaped by host factors and by its own nutrients, increasing in diversity over time.

Gut microbiota variations in patients diagnosed with major depressive disorder-A systematic review

OBJECTIVE

The etiology of major depressive disorder (MDD) is multi-factorial and has been associated with a perturbed gut microbiota. Thus, it is therefore of great importance to determine any variations in gut microbiota in patients with MDD.

METHODS

A systematic literature search was conducted including original research articles based on gut microbiota studies performed in patients with MDD. Demographic and clinical characteristics, applied methodology and observed gut microbiota composition were compared between included studies.

RESULTS

Seventeen studies were included with a total of 738 patients with MDD and 782 healthy controls using different DNA purification methods, sequencing platforms and data analysis models. Four studies found a reduced α-diversity in patients with MDD, while gut microbiota compositions clustered separately according to β-diversity between patients and controls in twelve studies. Additionally, there was an increase in relative abundance of Eggerthella, Atopobium, and Bifidobacterium and a decreased relative abundance of Faecalibacterium in patients with MDD compared with healthy controls.

CONCLUSION

Gut microbiota differs significantly when comparing patients with MDD and healthy controls, though inconsistently across studies. The heterogeneity in gut microbiota compositions between the studies may be explained by variations in study design.

Altered Gut Microbiota Related to Inflammatory Responses in Patients With Huntington's Disease

Emerging evidence indicates that gut dysbiosis may play a regulatory role in the onset and progression of Huntington’s disease (HD). However, any alterations in the fecal microbiome of HD patients and its relation to the host cytokine response remain unknown. The present study investigated alterations and host cytokine responses in patients with HD. We enrolled 33 HD patients and 33 sex- and age- matched healthy controls. Fecal microbiota communities were determined through 16S ribosomal DNA gene sequencing, from which we analyzed fecal microbial richness, evenness, structure, and differential abundance of individual taxa between HD patients and healthy controls. HD patients were evaluated for their clinical characteristics, and the relationships of fecal microbiota with these clinical characteristics were analyzed. Plasma concentrations of interferon gamma (IFN-γ), interleukin 1 beta (IL-1β), IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, and tumor necrosis factor alpha were measured by Meso Scale Discovery (MSD) assays, and relationships between microbiota and cytokine levels were analyzed in the HD group. HD patients showed increased α-diversity (richness), β-diversity (structure), and altered relative abundances of several taxa compared to those in healthy controls. HD-associated clinical characteristics correlated with the abundances of components of fecal microbiota at the genus level. Genus Intestinimonas was correlated with total functional capacity scores and IL-4 levels. Our present study also revealed that genus Bilophila were negatively correlated with proinflammatory IL-6 levels. Taken together, our present study represents the first to demonstrate alterations in fecal microbiota and inflammatory cytokine responses in HD patients. Further elucidation of interactions between microbial and host immune responses may help to better understand the pathogenesis of HD.

Plasma Metabolomics Profiling of Metabolic Pathways Affected by Major Depressive Disorder

Background: Major depressive disorder (MDD) is a common disease which is complicated by metabolic disorder. Although MDD has been studied relatively intensively, its metabolism is yet to be elucidated. Methods: To profile the global pathophysiological processes of MDD patients, we used metabolomics to identify differential metabolites and applied a new database Metabolite set enrichment analysis (MSEA) to discover dysfunctions of metabolic pathways of this disease. Hydrophilic metabolomics were applied to identify metabolites by profiling the plasma from 55 MDD patients and 100 sex-, gender-, BMI-matched healthy controls. The metabolites were then analyzed in MSEA in an attempt to discover different metabolic pathways. To investigate dysregulated pathways, we further divided MDD patients into two cohorts: (1) MDD patients with anxiety symptoms and (2) MDD patients without anxiety symptoms. Results: Metabolites which were hit in those pathways correlated with depressive and anxiety symptoms. Altogether, 17 metabolic pathways were enriched in MDD patients, and 23 metabolites were hit in those pathways. Three metabolic pathways were enriched in MDD patients without anxiety, including glycine and serine metabolism, arginine and proline metabolism, and phenylalanine and tyrosine metabolism. In addition, L-glutamic acid was positively correlated with the severity of depression and retardation if hit in MDD patients without anxiety symptoms. Conclusions: Different kinds of metabolic pathophysiological processes were found in MDD patients. Disorder of glycine and serine metabolism was observed in both MDD patients with anxiety and those without.

Gut Microbiome: A Potential Indicator for Differential Diagnosis of Major Depressive Disorder and General Anxiety Disorder

Background: Major depressive disorder (MDD) and general anxiety disorder (GAD) share many common features, leading to numerous challenges in their differential diagnosis. Given the importance of the microbiota-gut-brain axis, we investigated the differences in gut microbiota between representative cases of these two diseases and sought to develop a microbiome-based approach for their differential diagnosis. Methods: We enrolled 23 patients with MDD, 21 with GAD, and 10 healthy subjects (healthy crowd, HC) in the present study. We used 16S rRNA gene-sequencing analysis to determine the microbial compositions of the gut microbiome based on Illumina Miseq and according to the standard protocol. Results: GAD showed a significant difference in microbiota richness and diversity as compared with HC. Additionally, Otu24167, Otu19140, and Otu19751 were significantly decreased in MDD relative to HC, and Otu2581 and Otu10585 were significantly increased in GAD relative to MDD. At the genus level, the abundances of Sutterella and Fusicatenibacter were significantly lower in MDD relative to HC, and the abundances of Fusicatenibacter and Christensenellaceae_R7_group were significantly lower in GAD than in HC. The abundance of Sutterella was significantly higher whereas that of Faecalibacterium was significantly lower in GAD relative to MDD. Moreover, we observed that Christensenellaceae_R7_group negatively correlated with the factor score (Limited to Hopelessness) and total score of HAMD-24 (p < 0.05), whereas Fusicatenibacter negatively correlated with FT4 (p < 0.05). Furthermore, the GAD group showed significant differences at the genus level for Faecalibacterium, which negatively correlated with PTC (p < 0.05). Conclusions: This study elucidated a unique gut-microbiome signature associated with MDD and GAD that could facilitate differential diagnosis and targeted therapy.

Gut Microbiome Composition Associated With Major Depressive Disorder and Sleep Quality

The microbiota-gut-brain axis plays a critical role in the pathogenesis of major depressive disorder (MDD) and related subclinical symptoms. However, studies on the gut microbiota in MDD are inconsistent, and data on MDD's effects on sleep are lacking. This study aimed to analyze the gut microbiota composition and sleep quality of patients with MDD. We performed 16S rRNA sequencing of stool samples from 36 patients with MDD and 45 healthy controls (HC). Sleep quality was assessed using the Pittsburgh Sleep Quality Index, depressive severity with the Hamilton Depression Scale, and insomnia severity using the Insomnia Severity Index. Forty-eight microbiota targets showed significant differences between MDD and HC. In MDD, six microbiota targets were associated with the severity of depression, 11 with sleep quality, and 3 with sleep severity. At the genus level, Dorea was simultaneously related to depression and sleep quality, while Intestinibacter was more closely related to sleep problems. Coprococcus and Intestinibacter were associated with sleep quality independent of the severity of depression. In conclusion, the present findings enable a better understanding of the relationship between gut microbiota and MDD-related symptoms. Gut microbiota alterations may become potential biomarkers and/or treatment targets for sleep quality in MDD.

Virulence factor-related gut microbiota genes and immunoglobulin A levels as novel markers for machine learning-based classification of autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition for which early identification and intervention is crucial for optimum prognosis. Our previous work showed gut Immunoglobulin A (IgA) to be significantly elevated in the gut lumen of children with ASD compared to typically developing (TD) children. Gut microbiota variations have been reported in ASD, yet not much is known about virulence factor-related gut microbiota (VFGM) genes. Upon determining the VFGM genes distinguishing ASD from TD, this study is the first to utilize VFGM genes and IgA levels for a machine learning-based classification of ASD. Sequence comparisons were performed of metagenome datasets from children with ASD (n = 43) and TD children (n = 31) against genes in the virulence factor database. VFGM gene composition was associated with ASD phenotype. VFGM gene diversity was higher in children with ASD and positively correlated with IgA content. As Group B streptococcus (GBS) genes account for the highest proportion of 24 different VFGMs between ASD and TD and positively correlate with gut IgA, GBS genes were used in combination with IgA and VFGMs diversity to distinguish ASD from TD. Given that VFGM diversity, increases in IgA, and ASD-enriched VFGM genes were independent of sex and gastrointestinal symptoms, a classification method utilizing them will not pertain only to a specific subgroup of ASD. By introducing the classification value of VFGM genes and considering that VFs can be isolated in pregnant women and newborns, these findings provide a novel machine learning-based early risk identification method for ASD.

Gut Biofactory-Neurocompetent Metabolites within the Gastrointestinal Tract. A Scoping Review

The gut microbiota have gained much scientific attention recently. Apart from unravelling the taxonomic data, we should understand how the altered microbiota structure corresponds to functions of this complex ecosystem. The metabolites of intestinal microorganisms, especially bacteria, exert pleiotropic effects on the human organism and contribute to the host systemic balance. These molecules play key roles in regulating immune and metabolic processes. A subset of them affect the gut brain axis signaling and balance the mental wellbeing. Neurotransmitters, short chain fatty acids, tryptophan catabolites, bile acids and phosphatidylcholine, choline, serotonin, and L-carnitine metabolites possess high neuroactive potential. A scoping literature search in PubMed/Embase was conducted up until 20 June 2020, using three major search terms "microbiota metabolites" AND "gut brain axis" AND "mental health". This review aimed to enhance our knowledge regarding the gut microbiota functional capacity, and support current and future attempts to create new compounds for future clinical interventions.

Exploring the Role of Gut Microbiota in Major Depressive Disorder and in Treatment Resistance to Antidepressants

Major depressive disorder (MDD) is a common severe psychiatric illness, exhibiting sub-optimal response to existing pharmacological treatments. Although its etiopathogenesis is still not completely understood, recent findings suggest that an altered composition of the gut microbiota might play a role. Here we aimed to explore potential differences in the composition of the gut microbiota between patients with MDD and healthy controls (HC) and to identify possible signatures of treatment response by analyzing two groups of MDD patients characterized as treatment-resistant (TR) or responders (R) to antidepressants. Stool samples were collected from 34 MDD patients (8 TR, 19 R and 7 untreated) and 20 HC. Microbiota was characterized using the 16S metagenomic approach. A penalized logistic regression analysis algorithm was applied to identify bacterial populations that best discriminate the diagnostic groups. Statistically significant differences were identified for the families of Paenibacillaceae and Flavobacteriaceaea, for the genus Fenollaria, and the species Flintibacter butyricus, Christensenella timonensis, and Eisenbergiella massiliensis among others. The phyla Proteobacteria, Tenericutes and the family Peptostreptococcaceae were more abundant in TR, whereas the phylum Actinobacteria was enriched in R patients. Moreover, a number of bacteria only characterized the microbiota of TR patients, and many others were only detected in R. Our results confirm that dysbiosis is a hallmark of MDD and suggest that microbiota of TR patients significantly differs from responders to antidepressants. This finding further supports the relevance of an altered composition of the gut microbiota in the etiopathogenesis of MDD, suggesting a role in response to antidepressants.

Milk fermented with Lactococcus lactis KLDS4.0325 alleviates folate status in deficient mice

Folate is an essential B vitamin and its deficiency is common in many parts of the world. Natural folate produced by microorganisms may be an alternative to chemically synthesized folic acid (FA) as a dietary supplement. Previously, two lactic acid bacteria (LAB) strains, a high folate-producing Lactococcus lactis subsp. lactis KLDS4.0325 and a weak folate-producing Lactococcus lactis subsp. lactis KLDS4.0613, were identified. The aim of this study was to evaluate the effect of milk fermented with L. lactis KLDS4.0325 (folate-enriched fermented milk, FEFM) in alleviating folate deficiency status using murine folate deficiency models. In addition, the link between gut microbiota diversity and folate levels in mice was investigated. Results showed that FEFM increased FA and 5-methyltetrahydrofolate (5-MTHF) concentrations in the whole blood and liver, and decreased plasma homocysteine (Hcy) levels. 16S rDNA sequence analysis also revealed that the supplementation of FEFM (containing 0.6 μg mL^-1 folate) and 0.6 μg d^-1 FA (FEFM + LFA) significantly improved the poor status of the gut microbiota composition caused by folate deficiency, and the effect was better than that with 1.2 μg d^-1 FA (HFA) supplementation. Our findings show that FEFM can be used as a folate-fortified food to alleviate folate deficiency effectively. In addition, it may be considered as a partial or total replacement for synthetic FA.