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The intricate processes of microbiota-gut-brain communication in modulating human cognition and emotion, especially in the context of mood disorders, have remained elusive. Here we performed faecal metagenomic, serum metabolomics and neuroimaging studies on a cohort of 109 unmedicated patients with depressed bipolar disorder (BD) patients and 40 healthy controls (HCs) to characterise the microbial-gut-brain axis in BD. Across over 12,000 measured metabolic features, we observed a large discrepancy (73.54%) in the serum metabolome between BD patients and HCs, spotting differentially abundant microbial-derived neuroactive metabolites including multiple B-vitamins, kynurenic acid, gamma-aminobutyric acid and short-chain fatty acids. These metabolites could be linked to the abundance of gut microbiota presented with corresponding biosynthetic potentials, including Akkermansia muciniphila, Citrobacter spp. (Citrobacter freundii and Citrobacter werkmanii), Phascolarctobacterium spp., Yersinia spp. (Yersinia frederiksenii and Yersinia aleksiciae), Enterobacter spp. (Enterobacter cloacae and Enterobacter kobei) and Flavobacterium spp. Based on functional neuroimaging, BD-related neuroactive microbes and metabolites were discovered as potential markers associated with BD-typical features of functional connectivity of brain networks, hinting at aberrant cognitive function, emotion regulation, and interoception. Our study combines gut microbiota and neuroactive metabolites with brain functional connectivity, thereby revealing potential signalling pathways from the microbiota to the gut and the brain, which may have a role in the pathophysiology of BD.

SummaryRespiratory diseases impose an immense health burden worldwide. Epidemiological studies have revealed extensive disparities in the incidence and severity of respiratory tract infections (RTIs) between males and females. It is recently hypothesized that there might also be a nasal microbiome axis contributing to the observed sex disparities, but without evidence. In this work, we study the nasal microbiome of healthy young adults in, as of today, the largest cohort based on deep shot-gun metagenomic sequencing. We mainly focus on the bacteriome, but also integrate the mycobiome to get a more holistic perspective. De novo assembly is performed to catalog the nasal bacterial colonizers/residents, which also identify and therefore account for uncharacterized components of the community. The bacteriome is then profiled based on the non-redundant metagenome-assembled genomes (MAGs) catalog constructed therefrom. Unsupervised clustering reveals clearly separable structural patterns in the nasal microbiome between the two sexes. Following this link, we systematically evaluate sex differences for the first time and reveal extensive sex-specific features in the nasal microbiome composition. More importantly, through network analyses, we capture markedly higher ecological stability and antagonistic potentials in the nasal microbiome of females than that of males. The analysis of the keystone bacteria of the communities reveal that the sex-dependent evolutionary characteristics might have contributed to this difference.HighlightsThe non-redundant nasal bacterial MAGs catalog constructed from ultra-deeply sequenced metagenomic data provides a valuable resource.Integrating nasal bacteriome and mycobiome data provides a more holistic perspective for the understudied human nasal microbiome.Unsupervised clustering helps uncover extensive sex differences in the nasal microbiome compositions.Network analyses capture markedly higher ecological stability and antagonistic potentials in the nasal microbiome of females than that of males.Sex-dependent genetic evolutionary forces play a role in the shaping of keystones in the nasal microbial community.

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Saliva is a complex biological fluid with a variety of biomolecules, such as DNA, RNA, proteins, metabolites and microbiota, which can be used for the screening and diagnosis of many diseases. In addition, saliva has the characteristics of simple collection, non-invasive and convenient storage, which gives it the potential to replace blood as a new main body of fluid biopsy, and it is an excellent biological diagnostic fluid. This review integrates recent studies and summarizes the research contents of salivaomics and the research progress of saliva in early diagnosis of oral and systemic diseases. This review aims to explore the value and prospect of saliva diagnosis in clinical application.

The human oral cavity is a hotspot of numerous, mostly unexplored, viruses that are important for maintaining oral health and microbiome homeostasis. Here, we analyzed 2,792 publicly available oral metagenomes and proposed the Oral Virus Database (OVD) comprising 48,425 nonredundant viral genomes (≥5 kbp). The OVD catalog substantially expanded the known phylogenetic diversity and host specificity of oral viruses, allowing for enhanced delineation of some underrepresented groups such as the predicted Saccharibacteria phages and jumbo viruses. Comparisons of the viral diversity and abundance of different oral cavity habitats suggested strong niche specialization of viromes within individuals. The virome variations in relation to host geography and properties were further uncovered, especially the age-dependent viral compositional signatures in saliva. Overall, the viral genome catalog describes the architecture and variability of the human oral virome, while offering new resources and insights for current and future studies.

The oral microbiota contains billions of microbial cells, which could contribute to diseases in many body sites. Challenged by eating, drinking, and dental hygiene on a daily basis, the oral microbiota is regarded as highly dynamic. Here, we report significant human genomic associations with the oral metagenome from more than 1915 individuals, for both the tongue dorsum (n = 2017) and saliva (n = 1915). We identified five genetic loci associated with oral microbiota at study-wide significance (p −11). Four of the five associations were well replicated in an independent cohort of 1439 individuals: rs1196764 at APPL2 with Prevotella jejuni, Oribacterium uSGB 3339 and Solobacterium uSGB 315; rs3775944 at the serum uric acid transporter SLC2A9 with Oribacterium uSGB 1215, Oribacterium uSGB 489 and Lachnoanaerobaculum umeaense; rs4911713 near OR11H1 with species F0422 uSGB 392; and rs36186689 at LOC105371703 with Eggerthia. Further analyses confirmed 84% (386/455 for tongue dorsum) and 85% (391/466 for saliva) of host genome-microbiome associations including six genome-wide significant associations mutually validated between the two niches. As many of the oral microbiome-associated genetic variants lie near miRNA genes, we tentatively validated the potential of host miRNAs to modulate the growth of specific oral bacteria. Human genetics accounted for at least 10% of oral microbiome compositions between individuals. Machine learning models showed that polygenetic risk scores dominated over oral microbiome in predicting risk of dental diseases such as dental calculus and gingival bleeding. These findings indicate that human genetic differences are one explanation for a stable or recurrent oral microbiome in each individual.

Accumulating evidence suggests that gut microbiota plays a role in the pathogenesis of schizophrenia via the microbiota-gut-brain axis. This study sought to investigate whether transplantation of fecal microbiota from drug-free patients with schizophrenia into specific pathogen-free mice could cause schizophrenia-like behavioral abnormalities. The results revealed that transplantation of fecal microbiota from schizophrenic patients into antibiotic-treated mice caused behavioral abnormalities such as psychomotor hyperactivity, impaired learning and memory in the recipient animals. These mice also showed elevation of the kynurenine-kynurenic acid pathway of tryptophan degradation in both periphery and brain, as well as increased basal extracellular dopamine in prefrontal cortex and 5-hydroxytryptamine in hippocampus, compared with their counterparts receiving feces from healthy controls. Furthermore, colonic luminal filtrates from the mice transplanted with patients' fecal microbiota increased both kynurenic acid synthesis and kynurenine aminotransferase II activity in cultured hepatocytes and forebrain cortical slices. Sixty species of donor-derived bacteria showed significant difference between the mice colonized with the patients' and the controls' fecal microbiota, highlighting 78 differentially enriched functional modules including tryptophan biosynthesis function. In conclusion, our study suggests that the abnormalities in the composition of gut microbiota contribute to the pathogenesis of schizophrenia partially through the manipulation of tryptophan-kynurenine metabolism.

Reference genomes are essential for metagenomic analyses and functional characterization of the human gut microbiota. We present the Culturable Genome Reference (CGR), a collection of 1,520 nonredundant, high-quality draft genomes generated from >6,000 bacteria cultivated from fecal samples of healthy humans. Of the 1,520 genomes, which were chosen to cover all major bacterial phyla and genera in the human gut, 264 are not represented in existing reference genome catalogs. We show that this increase in the number of reference bacterial genomes improves the rate of mapping metagenomic sequencing reads from 50% to >70%, enabling higher-resolution descriptions of the human gut microbiome. We use the CGR genomes to annotate functions of 338 bacterial species, showing the utility of this resource for functional studies. We also carry out a pan-genome analysis of 38 important human gut species, which reveals the diversity and specificity of functional enrichment between their core and dispensable genomes., A resource of >1,500 bacterial reference genomes sheds light on the human gut microbiome.

Background The human skin microbiota is considered to be essential for skin homeostasis and barrier function. Comprehensive analyses of its function would substantially benefit from a catalog of reference genes derived from metagenomic sequencing. The existing catalog for the human skin microbiome is based on samples from limited individuals from a single cohort on reference genomes, which limits the coverage of global skin microbiome diversity. Results In the present study, we have used shotgun metagenomics to newly sequence 822 skin samples from Han Chinese, which were subsequently combined with 538 previously sequenced North American samples to construct an integrated Human Skin Microbial Gene Catalog (iHSMGC). The iHSMGC comprised 10,930,638 genes with the detection of 4,879,024 new genes. Characterization of the human skin resistome based on iHSMGC confirmed that skin commensals, such as Staphylococcus spp, are an important reservoir of antibiotic resistance genes (ARGs). Further analyses of skin microbial ARGs detected microbe-specific and skin site-specific ARG signatures. Of note, the abundance of ARGs was significantly higher in Chinese than Americans, while multidrug-resistant bacteria (“superbugs”) existed on the skin of both Americans and Chinese. A detailed analysis of microbial signatures identified Moraxella osloensis as a species specific for Chinese skin. Importantly, Moraxella osloensis proved to be a signature species for one of two robust patterns of microbial networks present on Chinese skin, with Cutibacterium acnes indicating the second one. Each of such “cutotypes” was associated with distinct patterns of data-driven marker genes, functional modules, and host skin properties. The two cutotypes markedly differed in functional modules related to their metabolic characteristics, indicating that host-dependent trophic chains might underlie their development. Conclusions The development of the iHSMGC will facilitate further studies on the human skin microbiome. In the present study, it was used to further characterize the human skin resistome. It also allowed to discover the existence of two cutotypes on the human skin. The latter finding will contribute to a better understanding of the interpersonal complexity of the skin microbiome.

Additional file 4: Figure S3. Evaluation of iHSMGC integrity. Genome coverage of (a) Malassezia sp., (b) top 10 genera of fungi, (c) top 25 genera of viruses, (d) top 60 genera of prokaryotes, each dot in (b-d) represents a species in the genera. Genome coverage of (e) Cutibacterium sp. and Staphylococcus sp., (f) Moraxella sp. and (g) Streptococcus sp.

Additional file 6: Figure S5. Factors correlated with drug resistance potential in Chinese. a, Bar chart comparing the explained variance (R2) of factors impacting the relative abundance of ARGs using the Adonis test. The L-value represents skin color from dark to white, the b-value is skin color from blue to yellow. b, Bar chart depicting the types of antibiotics corrected with age by the Spearman correlation. c, Bar chart showing the correlation with skincare habit (p < 0.05).

Most of the disease studies for the gut microbiome have collected cases and control samples from the elderly or the middle-aged. Despite general interest in microbiome health, it is not known how microbial biomarkers from metagenome-wide association studies (MWAS) would perform in a cohort of young individuals, who would be largely free of chronic diseases, as well as medication. Here we analyze high-depth fecal metagenomic shotgun sequencing for 2183 healthy adults with clinical parameters, diet, lifestyle, and metabolite measurements. We provide the first set of large-scale evidence for gut microbiome dysbiosis in hyperuricemia, which relates to meat intake. We build a cardiometabolic disease risk model based on gut microbes for initial screening in a young population and confirm the validity using external cohorts. Fecal bacteria that have been reported to be enriched in colorectal cancer (CRC) are found to correlate with methylhistidines, branched-chain amino acids (BCAA), aromatic amino acids and glutamic acid in these young individuals, which were validated by an additional cohort of 1404 individuals. Our comprehensive data suggest that the gut microbiome could show trends towards diseases years before onset, and the results lay the foundation for the design of larger screens for cardiometabolic diseases and CRC with clinically meaningful cutoffs.

More than a decade of gut microbiome studies have a common goal of improving human health. However, while most of the disease studies have focused on the elderly or the middle-aged, a reference cohort for the gut microbiome in young individuals has been lacking. It is also not clear what other omics data need to be measured to better understand the gut microbiome. Here, we present a cohort including 2183 adults with high-depth metagenomic shotgun sequencing data for the fecal microbiome and other omics data. In this multiomic cohort, we observe a number of vitamins, hormones, amino acids, and trace elements that correlated with the gut microbiome. Many of the associations are validated in an additional cohort consisting of 1404 individuals. Our comprehensive data are poised to provide advice to future populations and mechanistic study designs to better understand and manage our gut microbiome.

Additional file 2: Figure S1. Construction of the iHSMGC (integrated Human Skin Microbial Gene Catalog). The metagenomic sequencing data from the Chinese and North American cohorts were processed with an in-house pipeline to generate their respective gene catalogs. The two catalogs were merged to form a Two Cohorts nonredundant Gene Catalog (2CGC). Sequenced microbial genomes or draft genomes coverage by 2CGC were regarded as potentially containing sequences of human skin origin. Therefore, microbial genomes were filtered by 2CGC, and the retained microbial genomes were then used to generate the SGC. Finally, the 2CGC was merged with the skin gene catalog (SGC) to generate the iHSMGC.

Additional file 7: Figure S6. Differences in skin microbiota between Singapore Chinese and North Americans. a, Principal component analysis presenting the separation of skin microbiota of Singaporean Chinese (NCBI No. PRJNA277905) versus North Americans (HMP SRA bio-project 46333). The microbes, which were the main contributors to the separation, are indicated by arrows. b, The boxplot showing the prominent species that differ significantly in abundance between Singaporean Chinese and North Americans.

Additional file 12: Figure S11. Octylphenol polyethoxylates transformation and beta-carotene biosynthesis between the two skin cutotypes. a, Reaction step for the conversion of octylphenol polyethoxylates to alkylphenol ethoxylates. The histogram compares the abundance of the genes encode for the two enzymes within the two cutotypes (* p< 0.05, ** p < 0.01; Wilcoxon test). b, Reaction steps for the biosynthesis of beta-carotene in microorganisms. The green box represents the enrichment of the KOs in the M-cutotype, the white box represents no significant difference.

Additional file 3: Figure S2. Host information, coverage and completeness of the iHSMGC. a, Box plot comparing the reads mapping rate of the HMP dataset between HMP skin catalog and the iHSMGC. b, The Bee swarm plot showing the percentage of sequenced reads mapping to human hg19 of each sample. Different anatomical sites are indicated by different colors. c, Rarefaction curve based on gene profiles of 1,361 samples using the Chao2 estimator. d, Box plots demonstrating the read mapping rate from the dataset of Singapore Chinese (NCBI No. PRJNA277905), Italians (NCBI No. PRJNA281366) and another Singapore Chinese (NCBI No. PRJEB26427) by using the iHSMGC. AD-atopic dermatitis. Ea-External auditory canal, Ra-Retroarticular crease, Oc-Occiput, Ba-Back, Mb-Manubrium, Na-Nare, Ac-Antecubital fossa, Id-Interdigital web, Pc-Popliteal fossa, Ic-Inguinal crease, Vf-Volar forearm, Hp-Hypothenar palm, Tw-Toe webspace, Tn-Toenail, Ph-Plantar heel.

Additional file 5: Figure S4. Drug-resistant spectrum based on ARGs in different skin sites. a, Sankey diagram depicting the distribution of the top 15 types of antibiotics ranked by the corresponding ARG abundance. The height of the rectangles indicates the ARGs relative abundance against the corresponding drug resistance potential within the site. Each site and drug resistance potential is indicated in distinct colors. Fh-Forehead, Ck-Cheek, Ns-Nose, Ea-External auditory canal, Ra-Retroarticular crease, Oc-Occiput, Ba-Back, Mb-Manubrium, Na-Nare, Ac-Antecubital fossa, Id-Interdigital web, Pc-Popliteal fossa, Ic-Inguinal crease, Vf-Volar forearm, Hp-Hypothenar palm, Tw-Toe webspace, Tn-Toenail, Ph-Plantar heel. b-c, The pie chart showing the proportion of drug resistance (b) and resistance mechanisms (c). d, Principal component analysis indicating separation of drug-resistant spectrum within the different anatomical sites.

Additional file 8: Figure S7. Intraindividual differences are smaller than interindividual differences. Boxplots of Bray-Curtis distance depicts the similarity between anatomical sites in the face of the same individuals (intraindividual comparisons) or between the same/different sites of different individuals (interindividual comparisons). The left side of the dotted line shows the intraindividual differences, the right side the interindividual differences. The significance levels in the Wilcoxon rank-sum test are: +, p < 0.05; *, p < 0.01; **, p < 0.001.

The vagina contains at least a billion microbial cells, dominated by lactobacilli. Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age, as well as cervical, fecal, and salivary samples from a second cohort of 632 women. Factors such as pregnancy history, delivery history, cesarean section, and breastfeeding were all more important than menstrual cycle in shaping the microbiome, and such information would be necessary before trying to interpret differences between vagino-cervical microbiome data. Greater proportion of Bifidobacterium breve was seen with older age at sexual debut. The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history. Potential markers for lack of menstrual regularity, heavy flow, dysmenorrhea, and contraceptives were also identified. Lactobacilli were rare during breastfeeding or post-menopause. Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome. Gut and salivary microbiomes, plasma vitamins, metals, amino acids, and hormones showed associations with the vagino-cervical microbiome. Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth. The vagina contains at least a billion microbial cells, dominated by lactobacilli. Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age, as well as cervical, fecal, and salivary samples from a second cohort of 632 women. Factors such as pregnancy history, delivery history, cesarean section, and breastfeeding were all more important than menstrual cycle in shaping the microbiome, and such information would be necessary before trying to interpret differences between vagino-cervical microbiome data. Greater proportion of Bifidobacterium breve was seen with older age at sexual debut. The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history. Potential markers for lack of menstrual regularity, heavy flow, dysmenorrhea, and contraceptives were also identified. Lactobacilli were rare during breastfeeding or post-menopause. Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome. Gut and salivary microbiomes, plasma vitamins, metals, amino acids, and hormones showed associations with the vagino-cervical microbiome. Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth.

The vaginal microbiota is less complex than the gut microbiota, and the colonization of Lactobacillus in the female vagina is considered to be critical for reproductive health. Oral probiotics have been suggested as promising means to modulate vaginal homeostasis in the general population. In this study, 60 Chinese women were followed for over a year before, during, and after treatment with the probiotics Lactobacillus rhamnosus GR-1 and Lactobacillus reuteri RC-14. Shotgun metagenomic data of 1334 samples from multiple body sites did not support a colonization route of the probiotics from the oral cavity to the intestinal tract and then to the vagina. Our analyses enable the classification of the cervicovaginal microbiome into a stable state and a state of dysbiosis. The microbiome in the stable group steadily maintained a relatively high abundance of Lactobacilli over one year, which was not affected by probiotic intake, whereas in the dysbiosis group, the microbiota was more diverse and changed markedly over time. Data from a subset of the dysbiosis group suggests this subgroup possibly benefited from supplementation with the probiotics, indicating that probiotics supplementation can be prescribed for women in a subclinical microbiome setting of dysbiosis, providing opportunities for targeted and personalized microbiome reconstitution.

The gut microbiome has been established as a key environmental factor to health. Genetic influences on the gut microbiome have been reported, yet, doubts remain as to the significance of genetic associations. Here, we provide shotgun data for whole genome and whole metagenome from a Chinese cohort, identifying no Prevotella–Bacteroides variances. Stratification according to gender led to the identification of differential associations in males and females. Our two-stage metagenome genome-wide association studies on a total of 1295 individuals unequivocally illustrates that neither microbiome nor GWAS studies could overlook one another in our quest for a better understanding of human health and diseases.

The gut microbiome has been implicated in a variety of physiological states. Controversy over causality, however, has always haunted microbiome studies. Here, we utilized the bidirectional Mendelian randomization (MR) approach to address questions that are not yet mature for more costly randomized interventions. From a total of 3,432 Chinese individuals with shotgun sequencing data for whole genome and whole metagenome, as well as anthropometric and blood metabolic traits, we identified 58 causal relationships between the gut microbiome and blood metabolites, and replicated 43 out of the 58. Gut microbiome could determine features in the blood. For example, increased fecal relative abundances of Oscillibacter and Alistipes were causally linked to decreased triglyceride concentration, and fecal microbial module pectin degradation might increase serum uric acid. On the other hand, blood features may determine gut microbial features, e.g. glutamic acid appeared to decrease Oxalobacter, and a few members of Proteobacteria were unidirectionally influenced by cardiometabolically important metabolites such as 5-methyltetrahydrofolic acid, alanine, as well as selenium. This study illustrates the value of human genetic information to help prioritize gut microbial features for mechanistic and clinical studies. The results are consistent with whole-body cross-talks of the microbiome and the circulating molecules.

Background & Aims Elucidating key factors affecting personal responses to food is the first step toward implementing personalized nutrition strategies in for example weight loss programs. Here, we aimed to identify factors of importance for individual weight loss trajectories in a natural setting where participants were provided dietary advice but otherwise asked to self-manage the daily caloric intake and data reporting. Methods A 6-month weight-reduction program with longitudinal collection of dietary, physical activity, body weight, and fecal microbiome data as well as single-nucleotide polymorphism genotypes in 83 participants was conducted, followed by integration of the high-dimensional data to define the most determining factors for weight loss in a dietician-guided, smartphone-assisted dieting program. Results The baseline gut microbiota was found to outperform other factors as a predieting predictor of individual weight loss trajectories. Weight loss was also linked to the magnitude of changes in abundances of certain bacterial species during dieting. Ruminococcus gnavus (MGS0160) was significantly enriched in obese individuals and decreased during weight loss. Akkermansia muciniphila (MGS0120) and Alistipes obesi (MGS0342) were significantly enriched in lean individuals, and their abundance increased during dieting. Finally, Blautia wexlerae (MGS0575) and Bacteroides dorei (MGS0187) were the strongest predictors for weight loss when present in high abundance at baseline. Conclusion Altogether, the baseline gut microbiota was found to excel as a central personal factor in capturing the relationship between dietary factors and weight loss among individuals on a dieting program.

The gut microbiome has been implicated in a variety of physiological states, but controversy over causality remains unresolved. Here, we performed bidirectional Mendelian randomization analyses on 3,432 Chinese individuals with whole-genome, whole-metagenome, anthropometric and blood metabolic trait data. We identified 58 causal relationships between the gut microbiome and blood metabolites, and replicated 43 of them. Increased relative abundances of fecal Oscillibacter and Alistipes were causally linked to decreased triglyceride concentration. Conversely, blood metabolites such as glutamic acid appeared to decrease fecal Oxalobacter, and members of Proteobacteria were influenced by metabolites such as 5-methyltetrahydrofolic acid, alanine, glutamate and selenium. Two-sample Mendelian randomization with data from Biobank Japan partly corroborated results with triglyceride and with uric acid, and also provided causal support for published fecal bacterial markers for cancer and cardiovascular diseases. This study illustrates the value of human genetic information to help prioritize gut microbial features for mechanistic and clinical studies.

Human urine is traditionally considered to be sterile, and whether the urine harbours distinct microbial communities has been a matter of debate. Potential links between female urine and reproductive tract microbial communities is currently not clear. Here, we collected urine samples from 147 Chinese women of reproductive age and explored the nature of colonization by 16S rRNA gene amplicon sequencing, quantitative real-time PCR, and live bacteria culture. To demonstrate the utility of this approach, the intra-individual Spearman’s correlation was used to explore the relationship between urine and multiple sites of the female reproductive tract. PERMANOVA was also performed to explore potential correlations between the lifestyle and various clinical factors and urinary bacterial communities. Our data demonstrated distinct bacterial communities in urine, indicative of a non-sterile environment. Streptococcus-dominated, Lactobacillus-dominated, and diverse type were the three most common urinary bacterial community types in the cohort. Detailed comparison of the urinary microbiota with multiple sites of the female reproductive tract microbiota demonstrated that the urinary microbiota were more similar to the microbiota in the cervix and uterine cavity than to those of the vagina in the same women. Our data demonstrate the potential connectivity among microbiota in the female urogenital system and provide insight and resources for exploring diseases of the urethra and genital tract.

Evidence is mounting that the gut-brain axis plays an important role in mental diseases fueling mechanistic investigations to provide a basis for future targeted interventions. However, shotgun metagenomic data from treatment-naïve patients are scarce hampering comprehensive analyses of the complex interaction between the gut microbiota and the brain. Here we explore the fecal microbiome based on 90 medication-free schizophrenia patients and 81 controls and identify a microbial species classifier distinguishing patients from controls with an area under the receiver operating characteristic curve (AUC) of 0.896, and replicate the microbiome-based disease classifier in 45 patients and 45 controls (AUC = 0.765). Functional potentials associated with schizophrenia include differences in short-chain fatty acids synthesis, tryptophan metabolism, and synthesis/degradation of neurotransmitters. Transplantation of a schizophrenia-enriched bacterium, Streptococcus vestibularis, appear to induces deficits in social behaviors, and alters neurotransmitter levels in peripheral tissues in recipient mice. Our findings provide new leads for further investigations in cohort studies and animal models., Gut microbiome has been linked to neurogenerative diseases. Here, the authors present a metagenome-wide association study of schizophrenia (SZ) in human cohorts and identify SZ-associated specific gut-brain functional modules and pathways including SCFAs and neurotransmitters.

Gut microbiome influenced many aspects of host physiology and psychology. Vice versa, lifestyles factors such as exercise and healthy diet are ways to shape the gut microbiota towards balance. We observed two distinct microbe groups characterized by physical fitness in a multi-omic cohort of 2183 young subjects with metagenomics, national physique comprehensive test, lifestyle and metabolome data. The panel of bacterial taxa including Clostridium bolteae, Escherichia coli, Ruminococcus gnavus, Clostridium clostridioforme, Clostridium innocuum, Bacteroides cellulosilyticus and Oscillospiraceae, were consistently associated with most of the physical fitness. Clostridium species and trace element both increased in the individuals those tend to stay up late. Yogurt consumption was associated with Streptococcus thermophilus and Bifidobacterium animalis subsp. lactis in feces, which differed from potentially endogenous Bifidobacterium species that was associated with milk intake. Our large-scale analyses were poised to advise for a healthy gut microbiome through behavioural changes.

The root microbes play pivotal roles in plant productivity, nutrient uptakes, and disease resistance. The root microbial community structure has been extensively investigated by 16S/18S/ITS amplicons and metagenomic sequencing in crops and model plants. However, the functional associations between root microbes and host plant growth are poorly understood. This work investigates the root bacterial community of foxtail millet (Setaria italica) and its potential effects on host plant productivity. We determined the bacterial composition of 2882 samples from foxtail millet rhizoplane, rhizosphere and corresponding bulk soils from 2 well-separated geographic locations by 16S rRNA gene amplicon sequencing. We identified 16 109 operational taxonomic units (OTUs), and defined 187 OTUs as shared rhizoplane core OTUs. The β-diversity analysis revealed that microhabitat was the major factor shaping foxtail millet root bacterial community, followed by geographic locations. Large-scale association analysis identified the potential beneficial bacteria correlated with plant high productivity. Besides, the functional prediction revealed specific pathways enriched in foxtail millet rhizoplane bacterial community. We systematically described the root bacterial community structure of foxtail millet and found its core rhizoplane bacterial members. Our results demonstrated that host plants enrich specific bacteria and functions in the rhizoplane. The potentially beneficial bacteria may serve as a valuable knowledge foundation for bio-fertilizer development in agriculture.