Strain-level dissection of the contribution of the gut microbiome to human metabolic disease

Bidirectional Link Between Exercise and the Gut Microbiota

Exercise is well known to exert beneficial changes to the gut microbiota. An emerging area is how the gut microbiota may regulate exercise tolerance. This review will summarize the current evidence on how exercise influences gut microbial communities, with emphasis on how disruptions or depletion of an intact gut microbiota impacts exercise tolerance as well as future directions.

The potential role of Akkermansia muciniphila in liver health

Akkermansia muciniphila (A. muciniphila) is a 'star strain' that has attracted much attention in recent years. A. muciniphila can effectively regulate host metabolism, significantly affect host immune function, and play an important role in balancing host health and disease. As one of the organs most closely related to the gut (the two can communicate through the hepatic portal vein and bile duct system), liver is widely affected by intestinal microorganisms. A growing body of evidence suggests that A. muciniphila may alleviate liver-related diseases by improving the intestinal barrier, energy metabolism and regulating inflammation through its protein components and metabolites. This paper systematically reviews the key roles of A. muciniphila and its derivatives in maintaining liver health and improving liver disease.

Mass Spectrometry Applications to Study Human Microbiome

Microbiotas are an adaptable component of ecosystems, including human ecology. Microorganisms influence the chemistry of their specialized niche, such as the human gut, as well as the chemistry of distant surroundings, such as other areas of the body. Metabolomics based on mass spectrometry (MS) is one of the primary methods for detecting and identifying small compounds generated by the human microbiota, as well as understanding the functional significance of these microbial metabolites. This book chapter gives basic knowledge on the kinds of untargeted mass spectrometry as well as the data types that may be generated in the context of microbiome study. While data analysis remains a barrier, the emphasis is on data analysis methodologies and integrative analysis, particularly the integration of microbiome sequencing data. Mass spectrometry (MS)-based techniques have resurrected culture methods for studying the human gut microbiota, filling in the gaps left by high-throughput sequencing methods in terms of culturing minor populations.

Parabacteroides distasonis ameliorates insulin resistance via activation of intestinal GPR109a

Gut microbiota plays a key role in insulin resistance (IR). Here we perform a case-control study of Chinese adults (ChiCTR2200065715) and identify that Parabacteroides distasonis is inversely correlated with IR. Treatment with P. distasonis improves IR, strengthens intestinal integrity, and reduces systemic inflammation in mice. We further demonstrate that P. distasonis-derived nicotinic acid (NA) is a vital bioactive molecule that fortifies intestinal barrier function via activating intestinal G-protein-coupled receptor 109a (GPR109a), leading to ameliorating IR. We also conduct a bioactive dietary fiber screening to induce P. distasonis growth. Dendrobium officinale polysaccharide (DOP) shows favorable growth-promoting effects on P. distasonis and protects against IR in mice simultaneously. Finally, the reduced P. distasonis and NA levels were also validated in another human type 2 diabetes mellitus cohort. These findings reveal the unique mechanisms of P. distasonis on IR and provide viable strategies for the treatment and prevention of IR by bioactive dietary fiber.

Microbial-host isozyme: A novel target in "drug the bug" strategies for diabetes

The role of the gut microbiome in metabolic diseases, such as diabetes, has emerged as a pivotal area of medical research. Wang et al.'s recent work reported that a gut bacteria-derived microbial-host isozyme, mimicking a human enzyme responsible for blood glucose regulation, can significantly impact the efficacy of diabetes medications.

Gut microbiota modulate distal symmetric polyneuropathy in patients with diabetes

The pathogenic mechanisms underlying distal symmetric polyneuropathy (DSPN), a common neuropathy in patients with diabetes mellitus (DM), are not fully understood. Here, we discover that the gut microbiota from patients with DSPN can induce a phenotype exhibiting more severe peripheral neuropathy in db/db mice. In a randomized, double-blind, and placebo-controlled trial (ChiCTR1800017257), compared to 10 patients who received placebo, DSPN was significantly alleviated in the 22 patients who received fecal microbiota transplants from healthy donors, independent of glycemic control. The gut bacterial genomes that correlated with the Toronto Clinical Scoring System (TCSS) score were organized in two competing guilds. Increased guild 1, which had higher capacity in butyrate production, and decreased guild 2, which harbored more genes in synthetic pathway of endotoxin, were associated with improved gut barrier integrity and decreased proinflammatory cytokine levels. Moreover, matched enterotype between transplants and recipients showed better therapeutic efficacy with more enriched guild 1 and suppressed guild 2. Thus, changes in these two competing guilds may play a causative role in DSPN and have the potential for therapeutic targeting.

Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis

Coronavirus disease 2019 (COVID-19) severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples from 300 in-hospital COVID-19 patients, collected at the time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), redundancy analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Co-abundance network analysis determined that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Based on average abundance difference between the two guilds, the guild-level microbiome index (GMI) classified patients from different severity groups (average AUROC [area under the receiver operating curve] = 0.83). Moreover, age-adjusted partial Spearman's correlation showed that GMIs at admission were correlated with 8 clinical parameters, which are predictors for COVID-19 prognosis, on day 7 in hospital. In addition, GMI at admission was associated with death/discharge outcome of the critical patients. We further validated that GMI was able to consistently classify patients with different COVID-19 symptom severities in different countries and differentiated COVID-19 patients from healthy subjects and pneumonia controls in four independent data sets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission. IMPORTANCE Previous reports on the associations between COVID-19 and gut microbiome have been constrained by taxonomic-level analysis and overlook the interaction between microbes. By applying a genome-resolved, reference-free, guild-based metagenomic analysis, we demonstrated that the relationship between gut microbiota and COVID-19 is genome-specific instead of taxon-specific or even species-specific. Moreover, the COVID-19-associated genomes were not independent but formed two competing guilds, with Guild 1 potentially beneficial and Guild 2 potentially more detrimental to the host based on comparative genomic analysis. The dominance of Guild 2 over Guild 1 at time of admission was associated with hospitalized COVID-19 patients at high risk for more severe outcomes. Moreover, the guild-level microbiome signature is not only correlated with the symptom severity of COVID-19 patients, but also differentiates COVID-19 patients from pneumonia controls and healthy subjects across different studies. Here, we showed the possibility of using genome-resolved and guild-level microbiome signatures to identify hospitalized COVID-19 patients with a high risk of more severe outcomes at the time of admission.

Fecal Microbiota, Forage Nutrients, and Metabolic Responses of Horses Grazing Warm- and Cool-Season Grass Pastures

Integrating warm-season grasses into cool-season equine grazing systems can increase pasture availability during summer months. The objective of this study was to evaluate effects of this management strategy on the fecal microbiome and relationships between fecal microbiota, forage nutrients, and metabolic responses of grazing horses. Fecal samples were collected from 8 mares after grazing cool-season pasture in spring, warm-season pasture in summer, and cool-season pasture in fall as well as after adaptation to standardized hay diets prior to spring grazing and at the end of the grazing season. Random forest classification was able to predict forage type based on microbial composition (accuracy: 0.90 ± 0.09); regression predicted forage crude protein (CP) and non-structural carbohydrate (NSC) concentrations (p < 0.0001). Akkermansia and Clostridium butyricum were enriched in horses grazing warm-season pasture and were positively correlated with CP and negatively with NSC; Clostridum butyricum was negatively correlated with peak plasma glucose concentrations following oral sugar tests (p ≤ 0.05). These results indicate that distinct shifts in the equine fecal microbiota occur in response different forages. Based on relationships identified between the microbiota, forage nutrients, and metabolic responses, further research should focus on the roles of Akkermansia spp. and Clostridium butyricum within the equine hindgut.

Machine learning model for predicting age in healthy individuals using age-related gut microbes and urine metabolites

Age-related gut microbes and urine metabolites were investigated in 568 healthy individuals using metataxonomics and metabolomics. The richness and evenness of the fecal microbiota significantly increased with age, and the abundance of 16 genera differed between the young and old groups. Additionally, 17 urine metabolites contributed to the differences between the young and old groups. Among the microbes that differed by age, Bacteroides and Prevotella 9 were confirmed to be correlated with some urine metabolites. The machine learning algorithm eXtreme gradient boosting (XGBoost) was shown to produce the best performing age predictors, with a mean absolute error of 5.48 years. The accuracy of the model improved to 4.93 years with the inclusion of urine metabolite data. This study shows that the gut microbiota and urine metabolic profiles can be used to predict the age of healthy individuals with relatively good accuracy.

Preventive Effects of Different Black and Dark Teas on Obesity and Non-Alcoholic Fatty Liver Disease and Modulate Gut Microbiota in High-Fat Diet Fed Mice

Non-alcoholic fatty liver disease (NAFLD) has emerged as a leading public health challenge and is closely associated with metabolic syndromes, such as obesity. Intestinal microbiota dysbiosis could play a vital role in the pathogenesis and progression of NAFLD. Tea is the second most popular health drink in the world behind water, and exhibits many health-promoting effects. In this study, the protective effects of different black and dark teas on NAFLD induced by long-term high-fat diet (HFD) exposure and their regulation of gut microbiota were evaluated and explored. The results indicated that supplementation with different black and dark tea extracts could significantly suppress the energy intake, alleviate abnormal accumulation of visceral fat, and prevent obesity, hepatic abnormal lipid deposition and liver steatosis in HFD-fed mice at varying degrees. In addition, Dianhong tea and Liupao tea interventions could significantly decrease the ratio of Firmicutes to Bacteroidetes, and selenium-enriched black tea and selenium-enriched dark rea supplementation could remarkably reduce the relative abundance of Actinobacteria compared to the model group. Moreover, these teas could partly shift the relative abundances of Allobaculum, Roseburia and Dubosiella. Taken together, black teas and dark teas could prevent HFD-induced features of obesity and NAFLD, which might partly be due to the modulation of gut microbiota.

Rational consideration of Akkermansia muciniphila targeting intestinal health: advantages and challenges

As one of the promising next-generation probiotics (NGPs), Akkermansia muciniphila, a well-known mucin-degrading bacterium, has been proven to be closely related to the metabolic diseases of its human host. However, the role of A. muciniphila in the host’s intestinal health remains ambiguous. Here, we comprehensively summarize and discuss the characteristics, the distribution, and the colonization of A. muciniphila in the human gastrointestinal tract (GIT). We propose that the application of A. muciniphila as a biomarker for longevity, for diagnostics and prognostics of intestinal diseases, or for intestinal health should be cautiously considered. Precise dietary regulation can mediate the treatment of intestinal diseases by altering the abundance of A. muciniphila. Although the beneficial role of A. muciniphila and its component in intestinal inflammation has been discovered, in gnotobiotic mice with specific gut microbiota, certain genotype, and colorectal cancer, or in animal models infected with a specific pathogen, A. muciniphila may be related to the occurrence and development of intestinal diseases. Genomic analysis, emphasizing the strain-level phylogenetic differences of A. muciniphila, indicates that a clear description and discussion of each strain is critical before its practical application. Our review provides much needed insight for the precise application of A. muciniphila.

StrainPanDA: Linked reconstruction of strain composition and gene content profiles via pangenome-based decomposition of metagenomic data

Microbial strains of variable functional capacities coexist in microbiomes. Current bioinformatics methods of strain analysis cannot provide the direct linkage between strain composition and their gene contents from metagenomic data. Here we present Strain-level Pangenome Decomposition Analysis (StrainPanDA), a novel method that uses the pangenome coverage profile of multiple metagenomic samples to simultaneously reconstruct the composition and gene content variation of coexisting strains in microbial communities. We systematically validate the accuracy and robustness of StrainPanDA using synthetic data sets. To demonstrate the power of gene-centric strain profiling, we then apply StrainPanDA to analyze the gut microbiome samples of infants, as well as patients treated with fecal microbiota transplantation. We show that the linked reconstruction of strain composition and gene content profiles is critical for understanding the relationship between microbial adaptation and strain-specific functions (e.g., nutrient utilization and pathogenicity). Finally, StrainPanDA has minimal requirements for computing resources and can be scaled to process multiple species in a community in parallel. In short, StrainPanDA can be applied to metagenomic data sets to detect the association between molecular functions and microbial/host phenotypes to formulate testable hypotheses and gain novel biological insights at the strain or subspecies level.

Fecal microbiome of horses transitioning between warm-season and cool-season grass pasture within integrated rotational grazing systems

BACKGROUND

Diet is a key driver of equine hindgut microbial community structure and composition. The aim of this study was to characterize shifts in the fecal microbiota of grazing horses during transitions between forage types within integrated warm- (WSG) and cool-season grass (CSG) rotational grazing systems (IRS). Eight mares were randomly assigned to two IRS containing mixed cool-season grass and one of two warm-season grasses: bermudagrass [Cynodon dactylon (L.) Pers.] or crabgrass [Digitaria sanguinalis (L.) Scop.]. Fecal samples were collected during transitions from CSG to WSG pasture sections (C-W) and WSG to CSG (W-C) on days 0, 2, 4, and 6 following pasture rotation and compared using 16S rRNA gene sequencing.

RESULTS

Regardless of IRS or transition (C-W vs. W-C), species richness was greater on day 4 and 6 in comparison to day 0 (P < 0.05). Evenness, however, did not differ by day. Weighted UniFrac also did not differ by day, and the most influential factor impacting β-diversity was the individual horse (R² ≥ 0.24; P = 0.0001). Random forest modeling was unable to accurately predict days within C-W and W-C, but could predict the individual horse based on microbial composition (accuracy: 0.92 ± 0.05). Only three differentially abundant bacterial co-abundance groups (BCG) were identified across days within all C-W and W-C for both IRS (W ≥ 126). The BCG differing by day for all transitions included amplicon sequence variants (ASV) assigned to bacterial groups with known fibrolytic and butyrate-producing functions including members of Lachnospiraceae, Clostridium sensu stricto 1, Anaerovorax the NK4A214 group of Oscillospiraceae, and Sarcina maxima. In comparison, 38 BCG were identified as differentially abundant by horse (W ≥ 704). The ASV in these groups were most commonly assigned to genera associated with degradation of structural carbohydrates included Rikenellaceae RC9 gut group, Treponema, Christensenellaceae R-7 group, and the NK4A214 group of Oscillospiraceae. Fecal pH also did not differ by day.

CONCLUSIONS

Overall, these results demonstrated a strong influence of individual horse on the fecal microbial community, particularly on the specific composition of fiber-degraders. The equine fecal microbiota were largely stable across transitions between forages within IRS suggesting that the equine gut microbiota adjusted at the individual level to the subtle dietary changes imposed by these transitions. This adaptive capacity indicates that horses can be managed in IRS without inducing gastrointestinal dysfunction.

Metabolic characteristics related to the hazardous effects of environmental arsenic on humans: A metabolomic review

Arsenic (As) is a toxic metalloid exist ubiquitously in environment. Epidemiological studies and laboratory animal studies have verified that As damages multiple organs or tissues in the body and is associated with a variety of diseases. Changes in metabolites usually indicate disturbances in metabolic pathways and specific metabolites are considered as biomarkers of diseases or drugs/toxins or environmental effects. Metabolomics is the quantitative measurement of the dynamic multi-parameter metabolic responses of biological systems due to pathophysiological or genetic changes. Current years, some metabolomic studies on the hazardous effect of environmental As on humans have been reported. In this paper, we first overviewed the metabolomics studies of environmental As exposure in humans since 2011, emphasizing on the data mining process of metabolic characteristics related to the hazardous effects of environmental As on humans. Then, the relationship between metabolic characteristics and the toxic mechanism of environmental As exposure in humans were discussed, and finally, the prospects of metabolomics studies on populations exposed to environmental As were put forward. Our paper may shed light on the study of mechanisms, prevention and individualized treatment of As poisoning.

Codonopsis pilosula Polysaccharide Improved Spleen Deficiency in Mice by Modulating Gut Microbiota and Energy Related Metabolisms

Codonopsis Radix (CR) is an important traditional Chinese medicine used for the treatment of spleen deficiency syndrome (SDS). Codonopsis pilosula polysaccharides (CPP) in CR are considered to be responsible for tonifying the spleen function; however, the mechanisms of the polysaccharides have remained unclear. This study aimed to investigate the treatment mechanisms of CPP in SDS mice using a combinational strategy of 16S rRNA gene sequencing and targeted metabolomics. Here, studies demonstrated that CPP had invigorating effect in vivo in Sennae Folium-induced SDS in mice by organ indexes, D-xylose determination, gastrointestinal hormones levels and goblet cells observation. Antibiotic treatment revealed that the intestinal microbiota was required for the invigorating spleen effect of CPP. Furthermore, gut microbiota analysis found that CPP significantly enriched probiotic Lactobacillus and decreased the abundance of some opportunistic pathogens, such as Enterococcus and Shigella. The metabolic profile analysis of the colonic content revealed that 25 chemicals were altered significantly by CPP, including amino acids, organic acids, fatty acids, carbohydrates and carnitine etc., which are mainly related to "energy conversion" related processes such as amino acids metabolism, tricarboxylic acid cycle, and nitrogen metabolism. Spearman's correlation assays displayed there were strong correlations among biochemical indicators-gut microbiota-metabolomics. In summary, these results provided a new perspective for CPP improving SDS by regulating energy metabolism related bacteria and pathways.

Network-based approaches for the investigation of microbial community structure and function using metagenomics-based data

Network-based approaches offer a powerful framework to evaluate microbial community organization and function as it relates to a variety of environmental processes. Emerging studies are exploring network theory as a method for data integration that is likely to be critical for the integration of 'omics' data using systems biology approaches. Intricacies of network theory and methodological and computational complexities in network construction, however, impede the use of these tools for translational science. We provide a perspective on the methods of network construction, interpretation and emerging uses for these techniques in understanding host-microbiota interactions.

A ribosomal operon database and MegaBLAST settings for strain-level resolution of microbiomes

Current methods to characterize microbial communities generally employ sequencing of the 16S rRNA gene (<500 bp) with high accuracy (∼99%) but limited phylogenetic resolution. However, long-read sequencing now allows for the profiling of near-full-length ribosomal operons (16S-ITS-23S rRNA genes) on platforms such as the Oxford Nanopore MinION. Here, we describe an rRNA operon database with >300 ,000 entries, representing >10 ,000 prokaryotic species and ∼ 150, 000 strains. Additionally, BLAST parameters were identified for strain-level resolution using in silico mutated, mock rRNA operon sequences (70-95% identity) from four bacterial phyla and two members of the Euryarchaeota, mimicking MinION reads. MegaBLAST settings were determined that required <3 s per read on a Mac Mini with strain-level resolution for sequences with >84% identity. These settings were tested on rRNA operon libraries from the human respiratory tract, farm/forest soils and marine sponges ( n = 1, 322, 818 reads for all sample sets). Most rRNA operon reads in this data set yielded best BLAST hits (95 ± 8%). However, only 38-82% of library reads were compatible with strain-level resolution, reflecting the dominance of human/biomedical-associated prokaryotic entries in the database. Since the MinION and the Mac Mini are both portable, this study demonstrates the possibility of rapid strain-level microbiome analysis in the field.

Cross-Sectional Study on the Gut Microbiome of Parkinson's Disease Patients in Central China

Gastrointestinal dysfunction plays an important role in the occurrence and development of Parkinson's disease (PD). This study investigates the composition of the gut microbiome using shotgun metagenomic sequencing in PD patients in central China. Fecal samples from 39 PD patients (PD group) and the corresponding 39 healthy spouses of the patients (SP) were collected for shotgun metagenomics sequencing. Results showed a significantly altered microbial composition in the PD patients. Bilophila wadsworthia enrichment was found in the gut microbiome of PD patients, which has not been reported in previous studies. The random forest (RF) model, which identifies differences in microbiomes, reliably discriminated patients with PD from controls; the area under the receiver operating characteristic curve was 0.803. Further analysis of the microbiome and clinical symptoms showed that Klebsiella and Parasutterella were positively correlated with the duration and severity of PD, whereas hydrogen-generating Prevotella was negatively correlated with disease severity. The Cluster of Orthologous Groups of protein database, the KEGG Orthology database, and the carbohydrate-active enzymes of gene-category analysis showed that branched-chain amino acid-related proteins were significantly increased, and GH43 was significantly reduced in the PD group. Functional analysis of the metagenome confirmed differences in microbiome metabolism in the PD group related to short-chain fatty acid precursor metabolism.

Associations between the gut microbiome and metabolome in early life

BACKGROUND

The infant intestinal microbiome plays an important role in metabolism and immune development with impacts on lifelong health. The linkage between the taxonomic composition of the microbiome and its metabolic phenotype is undefined and complicated by redundancies in the taxon-function relationship within microbial communities. To inform a more mechanistic understanding of the relationship between the microbiome and health, we performed an integrative statistical and machine learning-based analysis of microbe taxonomic structure and metabolic function in order to characterize the taxa-function relationship in early life.

RESULTS

Stool samples collected from infants enrolled in the New Hampshire Birth Cohort Study (NHBCS) at approximately 6-weeks (n = 158) and 12-months (n = 282) of age were profiled using targeted and untargeted nuclear magnetic resonance (NMR) spectroscopy as well as DNA sequencing of the V4-V5 hypervariable region from the bacterial 16S rRNA gene. There was significant inter-omic concordance based on Procrustes analysis (6 weeks: p = 0.056; 12 months: p = 0.001), however this association was no longer significant when accounting for phylogenetic relationships using generalized UniFrac distance metric (6 weeks: p = 0.376; 12 months: p = 0.069). Sparse canonical correlation analysis showed significant correlation, as well as identifying sets of microbe/metabolites driving microbiome-metabolome relatedness. Performance of machine learning models varied across different metabolites, with support vector machines (radial basis function kernel) being the consistently top ranked model. However, predictive R2 values demonstrated poor predictive performance across all models assessed (avg: - 5.06% -- 6 weeks; - 3.7% -- 12 months). Conversely, the Spearman correlation metric was higher (avg: 0.344-6 weeks; 0.265-12 months). This demonstrated that taxonomic relative abundance was not predictive of metabolite concentrations.

CONCLUSIONS

Our results suggest a degree of overall association between taxonomic profiles and metabolite concentrations. However, lack of predictive capacity for stool metabolic signatures reflects, in part, the possible role of functional redundancy in defining the taxa-function relationship in early life as well as the bidirectional nature of the microbiome-metabolome association. Our results provide evidence in favor of a multi-omic approach for microbiome studies, especially those focused on health outcomes.

Causal Inference in Microbiome Medicine: Principles and Applications

Microorganisms that colonize the mammalian skin and cavity play critical roles in various physiological functions of the host. Numerous studies have revealed strong associations between the microbiota and multiple diseases. However, association does not mean causation. To clarify the mechanisms underlying microbiota-mediated diseases, research is moving from associative analyses to causation studies. In this article, we first introduce the principles of the computational methods for causal inference, and then discuss the applications of these methods in microbiome medicine. Furthermore, we examine the reliability of theoretically inferred causality by the interventionist framework. Finally, we show the potential of confirmed causality in microbiota-targeted therapy, especially in personalized dietary intervention. We conclude that a comprehensive understanding of the causal relationships between diets, microbiota, host targets, and diseases is critical to future microbiome medicine.

Changes induced by chronic exposure to high arsenic concentrations in the intestine and its microenvironment

The perturbation of intestinal microbes may serve as a mechanism by which arsenic exposure causes or exacerbates diseases in humans. However, the changes in the intestinal microbiome and metabolome induced by long-term exposure to high concentrations of arsenic have not been extensively studied. In this study, C57BL/6 mice were exposed to sodium arsenite (As) (50 ppm) for 6 months. Our results show that long-term exposure to high As concentrations changed the structure of intestinal tissues and the expression of As resistance related genes in intestinal microbes. In addition, 16S rRNA gene sequencing revealed that As exposure significantly affected the Beta diversity of intestinal flora but had no significant effect on the Alpha diversity (except ACE index). Moreover, As exposure altered the composition of the intestinal microbiota from phylum to species. Non-targeted metabolomics profiling revealed that As exposure significantly changed the composition of metabolites, specifically those related to phenylalanine metabolism. Correlation analysis demonstrated that the changes in microbial communities and metabolites were highly correlated under As exposure. Overall, this study demonstrates that long-term exposure to high As concentrations disrupted the intestinal microbiome and metabolome, which may indicate the role of As exposure at inducing human diseases under similar conditions.

Guild-based analysis for understanding gut microbiome in human health and diseases

To demonstrate the causative role of gut microbiome in human health and diseases, we first need to identify, via next-generation sequencing, potentially important functional members associated with specific health outcomes and disease phenotypes. However, due to the strain-level genetic complexity of the gut microbiota, microbiome datasets are highly dimensional and highly sparse in nature, making it challenging to identify putative causative agents of a particular disease phenotype. Members of an ecosystem seldomly live independently from each other. Instead, they develop local interactions and form inter-member organizations to influence the ecosystem's higher-level patterns and functions. In the ecological study of macro-organisms, members are defined as belonging to the same "guild" if they exploit the same class of resources in a similar way or work together as a coherent functional group. Translating the concept of "guild" to the study of gut microbiota, we redefine guild as a group of bacteria that show consistent co-abundant behavior and likely to work together to contribute to the same ecological function. In this opinion article, we discuss how to use guilds as the aggregation unit to reduce dimensionality and sparsity in microbiome-wide association studies for identifying candidate gut bacteria that may causatively contribute to human health and diseases.

Active phase prebiotic feeding alters gut microbiota, induces weight-independent alleviation of hepatic steatosis and serum cholesterol in high-fat diet-fed mice

Growing evidence suggests that prebiotics may induce weight loss and alleviate non-alcoholic fatty liver disease (NAFLD) via modulation of the gut microbiota. However, key members of the gut microbiota that may mediate the beneficial effects of prebiotics remain elusive. Here, we find that restricted prebiotic feeding during active phase (HF-ARP) induced weight-independent alleviation of liver steatosis and reduced serum cholesterol in high-fat diet (HF) fed mice more significantly than unrestricted feeding (HF-UP). HF-ARP mice also showed concomitantly altered gut microbiota structure that was different from HF-UP group along with significantly increased production of total short-chain fatty-acids (SCFAs). Amplicon sequence variants (ASVs) were clustered into co-abundant groups (CAGs) as potential functional groups that may respond distinctively to prebiotic consumption and prebiotic feeding regime. Prebiotic feeding induces significant alterations in CAG abundances by day 7. Eight of 32 CAGs were promoted by prebiotics, including CAG17 with the most abundant ASV from Parabacteroides, CAG22 with Bacteroides thetaiotamicron and CAG32 with Fecalibaculum and Akkermansia. Among the prebiotic-promoted CAGs, CAG20 with ASVs from Lachnospiraceae and CAG21 with ASVs from Bifidobacterium and Lachnospiraceae were significantly enhanced in HF-ARP compared to HF-UP. Moreover, most of the prebiotic-promoted CAGs were also significantly associated with improvements in hepatic steatosis, reduction in serum cholesterol and increased cecal propionate production. Together, these results suggest that the impact of prebiotics on weight-independent alleviation of liver steatosis and cholesterol-lowering effect can be optimized by restricting prebiotic intake to active phase and is associated with a distinct change of gut microbiota with increased SCFA production.

Gut Bacteria Shared by Children and Their Mothers Associate with Developmental Level and Social Deficits in Autism Spectrum Disorder

Gut microbiota may contribute to the pathogenesis and development of autism spectrum disorder. The maternal gut microbiota influences offspring gut microbial structure and composition.

The gut microbiota of autism spectrum disorder (ASD) children differs from that of children without ASD. The maternal gut microbiota impacts offspring gut microbiota. However, the relationship between the development of ASD and gut bacteria shared between children and their mothers remains elusive. Our study recruited 76 children with ASD and 47 age- and gender-matched children with typical development (TD), as well as the mothers of both groups, and investigated their gut microbiota using amplicon sequence variants (ASVs). The gut microbiota of ASD children was altered compared with that of children with TD, while no significant alterations were found in their mothers. We established 30 gut bacterial coabundance groups (CAGs) and found the relative abundances of CAG15 and CAG16 significantly decreased in ASD children. CAG15 showed a positive correlation with developmental level. The proportion of ASD children who shared either one of the two Lachnospiraceae ASVs from CAG15 with their mothers was significantly lower than that of children with TD. Moreover, we found that CAG12, CAG13, and CAG18 negatively correlated with the severity of social deficits in ASD children. ASD children who shared any one of the four (two Ruminococcaceae, one Lachnospiraceae, and one Collinsella) ASVs in CAG13 and CAG18 with their mothers showed a lower level of social deficits than ASD children that did not share those with their mothers. These data demonstrate that these shared gut bacteria in ASD children are associated with their developmental level and social deficits. This work provides a new direction toward understanding the role of the gut microbiota in the pathogenesis and development of ASD. (This study has been registered in the Chinese Clinical Trial Registry under number ChiCTR-RPC-16008139.)

IMPORTANCE Gut microbiota may contribute to the pathogenesis and development of autism spectrum disorder. The maternal gut microbiota influences offspring gut microbial structure and composition. However, the relationship between the clinical symptoms of autism spectrum disorder and the gut bacteria shared between children and their mothers is not yet known. In our study, the gut microbiota of children with autism spectrum disorder differed from that of children with typical development, but there were no differences in the gut microbiota of their mothers. More importantly, gut bacteria shared between children with autism spectrum disorder and their mothers were related to developmental disabilities and social deficits. Thus, our study suggests that these shared gut bacteria may play an important role in the development of autism spectrum disorder. This provides a new direction for future studies aiming to explore the role of the gut microbiota in autism spectrum disorder.

Multiomics Study of Gut Bacteria and Host Metabolism in Irritable Bowel Syndrome and Depression Patients

Background and Aims

Irritable bowel syndrome (IBS) and depression have high tendencies of comorbidity. In particular, diarrhea-predominant IBS (IBS-D) and depression exhibit similar fecal microbiota signatures, yet little is known about their pathogenic mechanism. Here, we propose that the differences in structure and composition of IBS-D and depression gut microbiota give rise to different downstream functions, which lead to distinct clinical phenotypes via host metabolism and further influence the interaction of brain–gut axis.

Methods

We performed multiomics study, including fecal metagenome-wide sequencing and serum metabolomics profiling in 65 individuals with IBS-D (n=22), depression (n=15), comorbid patients (n=13), and healthy controls (n=15). We analyzed functional genes contributed by the primary genus and evaluated their correlations with clinical indices and host metabolites.

Results

Metagenomic analysis revealed 26 clusters of orthologous groups of protein (COG) categories consisting of a total of 4,631 functional genes. Trehalose and maltose hydrolase (COG1554) and fucose permease (COG0738) were the most relevant and enriched functional genes in the IBS-D patients; urease accessory proteins UreE (COG2371) was that in the depression patients. Context based genome annotation suggest that an alteration of Escherichia coli and Enterobacter cloacae in IBS-D and depression respectively may be responsible for the enrichment described above. Correlation with host metabolites, such as maltotriose and isomaltose in carbohydrate metabolism and anandamide in neuroactive metabolism, drew further connections between these findings.

Conclusions

These changes led us to propose a connection between genomic signatures and clinical differences observed in IBS-D and depression. Our findings provide further insights into the involvement of gut microbiota in diseases related to brain–gut disorder.

A predictive index for health status using species-level gut microbiome profiling

Providing insight into one’s health status from a gut microbiome sample is an important clinical goal in current human microbiome research. Herein, we introduce the Gut Microbiome Health Index (GMHI), a biologically-interpretable mathematical formula for predicting the likelihood of disease independent of the clinical diagnosis. GMHI is formulated upon 50 microbial species associated with healthy gut ecosystems. These species are identified through a multi-study, integrative analysis on 4347 human stool metagenomes from 34 published studies across healthy and 12 different nonhealthy conditions, i.e., disease or abnormal bodyweight. When demonstrated on our population-scale meta-dataset, GMHI is the most robust and consistent predictor of disease presence (or absence) compared to α-diversity indices. Validation on 679 samples from 9 additional studies results in a balanced accuracy of 73.7% in distinguishing healthy from non-healthy groups. Our findings suggest that gut taxonomic signatures can predict health status, and highlight how data sharing efforts can provide broadly applicable discoveries.

A biologically-interpretable and robust metric that provides insight into one’s health status from a gut microbiome sample is an important clinical goal in current human microbiome research. Herein, the authors introduce a species-level index that predicts the likelihood of having a disease.

Toxin-Antitoxin Systems: A Tool for Taxonomic Analysis of Human Intestinal Microbiota

The human gastrointestinal microbiota (HGM) is known for its rich diversity of bacterial species and strains. Yet many studies stop at characterizing the HGM at the family level. This is mainly due to lack of adequate methods for a high-resolution profiling of the HGM. One way to characterize the strain diversity of the HGM is to look for strain-specific functional markers. Here, we propose using type II toxin-antitoxin systems (TAS). To identify TAS systems in the HGM, we previously developed the software TAGMA. This software was designed to detect the TAS systems, MazEF and RelBE, in lactobacilli and bifidobacteria. In this study, we updated the gene catalog created previously and used it to test our software anew on 1346 strains of bacteria, which belonged to 489 species and 49 genera. We also sequenced the genomes of 20 fecal samples and analyzed the results with TAGMA. Although some differences were detected at the strain level, the results showed no particular difference in the bacterial species between our method and other classic analysis software. These results support the use of the updated catalog of genes encoding type II TAS as a useful tool for computer-assisted species and strain characterization of the HGM.

Host-Specific Evolutionary and Transmission Dynamics Shape the Functional Diversification of Staphylococcus epidermidis in Human Skin

Metagenomic inferences of bacterial strain diversity and infectious disease transmission studies largely assume a dominant, within-individual haplotype. We hypothesize that within-individual bacterial population diversity is critical for homeostasis of a healthy microbiome and infection risk. We characterized the evolutionary trajectory and functional distribution of Staphylococcus epidermidis-a keystone skin microbe and opportunistic pathogen. Analyzing 1,482 S. epidermidis genomes from 5 healthy individuals, we found that skin S. epidermidis isolates coalesce into multiple founder lineages rather than a single colonizer. Transmission events, natural selection, and pervasive horizontal gene transfer result in population admixture within skin sites and dissemination of antibiotic resistance genes within-individual. We provide experimental evidence for how admixture can modulate virulence and metabolism. Leveraging data on the contextual microbiome, we assess how interspecies interactions can shape genetic diversity and mobile gene elements. Our study provides insights into how within-individual evolution of human skin microbes shapes their functional diversification.

Endotoxin Producers Overgrowing in Human Gut Microbiota as the Causative Agents for Nonalcoholic Fatty Liver Disease

Recent studies have reported a link between gut microbiota and nonalcoholic fatty liver disease (NAFLD), showing that germfree (GF) mice do not develop metabolic syndromes, including NAFLD. However, the specific bacterial species causing NAFLD, as well as their molecular cross talk with the host for driving liver disease, remain elusive. Here, we found that nonvirulent endotoxin-producing strains of pathogenic species overgrowing in obese human gut can act as causative agents for induction of NAFLD and related metabolic disorders. The cross talk between endotoxin from these specific producers and the host’s TLR4 receptor is the most upstream and essential molecular event for inducing all phenotypes in NAFLD and related metabolic disorders. These nonvirulent endotoxin-producing strains of gut pathogenic species overgrowing in human gut may collectively become a predictive biomarker or serve as a novel therapeutic target for NAFLD and related metabolic disorders.

Gut microbiota-derived endotoxin has been linked to human nonalcoholic fatty liver disease (NAFLD), but the specific causative agents and their molecular mechanisms remain elusive. In this study, we investigated whether bacterial strains of endotoxin-producing pathogenic species overgrowing in obese human gut can work as causative agents for NAFLD. We further assessed the role of lipopolysaccharide (LPS)-Toll-like receptor 4 (TLR4) cross talk in this pathogenicity. Nonvirulent strains of Gram-negative pathobionts were isolated from obese human gut and monoassociated with C57BL/6J germfree (GF) mice fed a high-fat diet (HFD). Deletion of waaG in the bacterial endotoxin synthetic pathway and knockout of TLR4 in GF mice were used to further study the underlying mechanism for a causal relationship between these strains and the development of NAFLD. Three endotoxin-producing strains, Enterobacter cloacae B29, Escherichia coli PY102, and Klebsiella pneumoniae A7, overgrowing in the gut of morbidly obese volunteers with severe fatty liver, induced NAFLD when monoassociated with GF mice on HFD, while HFD alone did not induce the disease in GF mice. The commensal Bacteroides thetaiotaomicron (ATCC 29148), whose endotoxin activity was markedly lower than that of Enterobacteriaceae strains, did not induce NAFLD in GF mice. B29 lost its proinflammatory properties and NAFLD-inducing capacity upon deletion of the waaG gene. Moreover, E. cloacae B29 did not induce NAFLD in TLR4-deficient GF mice. These nonvirulent endotoxin-producing strains in pathobiont species overgrowing in human gut may work as causative agents, with LPS-TLR4 cross talk as the most upstream and essential molecular event for NAFLD.

Timing of Calorie Restriction in Mice Impacts Host Metabolic Phenotype with Correlative Changes in Gut Microbiota

Aberrant feeding patterns whereby people eat more frequently throughout the day and with a bias toward late-night eating are prevalent in society today. However, whether restriction of food to daytime in comparison to nighttime, coupled with restricted calorie intake, can influence gut microbiota, metabolism, and overall health requires further investigation. We surveyed the effects of the shift in feeding time on gut microbiota and metabolic phenotype in calorie-restricted mice and found that avoiding eating during the rest period may generate more beneficial effects in mice. This work strengthens the evidence for using “when to eat” as an intervention to improve health during calorie restriction.

Calorie restriction (CR) is accompanied by self-imposed daily restriction of food intake and an extended fasting period between meals. The impact of restricting feeding to the dark or light phase on the effects of CR remains elusive. Here, light-fed CR mice showed physiological changes, such as muscle loss, concomitant with changes in the gut microbiota structure and composition. After switching to ad libitum access to food, light-fed mice had a period of food-craving behavior and short-lived physiological changes, while dark-fed mice displayed lasting changes in fat accumulation, glucose metabolism, intestinal barrier function, and systemic inflammatory markers. Moreover, the gut microbiota was modulated by when the food was consumed, and the most abundant Lactobacillus operational taxonomic unit (OTU) promoted by CR was enhanced in dark-fed mice. After switching to ad libitum feeding, the gut microbiota of dark-fed mice returned to the state resembling that of mice fed normal chow ad libitum, but that of light-fed mice was still significantly different from the other two groups. Together, these data indicate that for CR, restricting food consumption to the active phase brought better metabolic phenotype associated with potentially beneficial structural shifts in the gut microbiota.

IMPORTANCE Aberrant feeding patterns whereby people eat more frequently throughout the day and with a bias toward late-night eating are prevalent in society today. However, whether restriction of food to daytime in comparison to nighttime, coupled with restricted calorie intake, can influence gut microbiota, metabolism, and overall health requires further investigation. We surveyed the effects of the shift in feeding time on gut microbiota and metabolic phenotype in calorie-restricted mice and found that avoiding eating during the rest period may generate more beneficial effects in mice. This work strengthens the evidence for using “when to eat” as an intervention to improve health during calorie restriction.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

Microstructure-modified products from stone-milled wheat bran powder improve glycemic response and sustain colonic fermentation

Accumulating evidence indicates carbohydrates that escape digestion from upper gastrointestinal tract can reduce glycemic response, enter the colon where they are fermented by the gut microbiota and thus exert multiple healthy benefits to host. A vertical stone milling process was used to prepare a natural wheat bran powder (SWB) containing pericarp, spermoderm, nucellar layer, aleurone layer, germ, and 15% starchy endosperm of wheat kernel, with the result that protein, amylose, and dietary fiber significantly raised comparing to wheat flour (WF). Two types of products, a powdered drink (SWB-D) and a puffed particle (SWB-P), were extruded from SWB, which underwent a gradient of gelatinization and recrystallization with progressively increased resistant starch (RS) content. Starch-protein complexes were detected in SWB-D and SWB-P, concurrently accounting for lower in vitro digestibility and human glycemic response than those of WF noodles. Intake of SWB-D and SWB-P by healthy volunteers elevated level and extended duration of breath hydrogen indicative of higher gut microbiota fermentation. Therefore, RS and starch-protein complexes formed during extrusion reduce digestibility of SWB and sustain colonic fermentation with health-promoting potential targeting the gut microbiota.

Escherichia coli Clonobiome: Assessing the Strain Diversity in Feces and Urine by Deep Amplicon Sequencing

While microbiome studies have focused on diversity at the species level or higher, bacterial species in microbiomes are represented by different, often multiple, strains. These strains could be clonally and phenotypically very different, making assessment of strain content vital to a full understanding of microbiome function. This is especially important with respect to antibiotic-resistant strains, the clonal spread of which may be dependent on competition between them and susceptible strains from the same species. The pandemic, multidrug-resistant, and highly pathogenic Escherichia coli subclone ST131-H30 (H30) is of special interest, as it has already been found persisting in the gut and bladder in healthy people. In order to rapidly assess E. coli clonal diversity, we developed a novel method based on deep sequencing of two loci used for sequence typing, along with an algorithm for analysis of the resulting data. Using this method, we assessed fecal and urinary samples from healthy women carrying H30 and were able to uncover considerable diversity, including strains with frequencies at <1% of the E. coli population. We also found that, even in the absence of antibiotic use, H30 could completely dominate the gut and, especially, urine of healthy carriers. Our study offers a novel tool for assessing a species' clonal diversity (clonobiome) within the microbiome, which could be useful in studying the population structure and dynamics of multidrug-resistant and/or highly pathogenic strains in their natural environments.IMPORTANCE Bacterial species in the microbiome are often represented by multiple genetically and phenotypically different strains, making insight into subspecies diversity critical to a full understanding of the microbiome, especially with respect to opportunistic pathogens. However, methods allowing efficient high-throughput clonal typing are not currently available. This study combines a conventional E. coli typing method with deep amplicon sequencing to allow analysis of many samples concurrently. While our method was developed for E. coli, it may be adapted for other species, allowing microbiome researchers to assess clonal strain diversity in natural samples. Since assessment of subspecies diversity is particularly important for understanding the spread of antibiotic resistance, we applied our method to the study of a pandemic multidrug-resistant E. coli clone. The results we present suggest that this clone could be highly competitive in healthy carriers and that the mechanisms of colonization by such clones need to be studied.

Edgeworthia gardneri (Wall.) Meisn. water extract improves diabetes and modulates gut microbiota

ETHNOPHARMACOLOGICAL RELEVANCE

In Chinese folk medicine, the flower of Edgeworthia gardneri (Wall.) Meisn. is used to treat various metabolic diseases, such as hyperglycemia, hypertension, and hyperlipidemia.

AIM OF THE STUDY

This study aimed to explore the antidiabetes potential of the flower of E. gardneri and investigate whether it can benefit the entire gut bacteria community.

MATERIALS AND METHODS

Chemical constituents of the extract were analyzed by UHPLC-Q Exactive Mass Spectrometer (UHPLC-QE-MS). The antidiabetes effect of the water extract (WAE) of the flower of E. gardneri was evaluated in diabetic mice induced by high-fat diet (HFD) and streptozotocin (STZ) (six groups, n = 8) daily at doses of 1, 2, and 3 g/kg for 4 weeks. The gut microbiota was analyzed using high-throughput 16S rRNA gene sequencing. Short-chain fatty acids (SCFAs) in the fecal were also investigated.

RESULTS

UHPLC-QE-MS analysis identified 29 compounds, including five alkaloids, six coumarins, four flavonoids, 11 organic acids, and three additional compounds, in the WAE. Results showed that the high dose of WAE considerably decreased the blood glucose level by 30.0%. Furthermore, E. gardneri significantly ameliorated insulin resistance and lipid metabolism dysfunction and repaired islet, hepatic, and white fat and colon histology in diabetic mice. Diabetic mice treated with WAE showed apparent changes in the structure and composition of the gut microbiota. WAE reversed the changes in Clostridiales, Lachnospiraceae, S24-7, Rikenellaceae, and Dorea in diabetic mice. The correlation analysis indicated that key OTUs were related to diabetes indices. The amounts of SCFAs, including acetic, propionic, and valeric acids, were significantly high in WAE-treated diabetic groups.

CONCLUSIONS

E. gardneri treatment improved the glucose metabolism and reshaped the unbalanced gut microbiota of diabetic mice. Our study provides evidence for application of E. gardneri to treatment of diabetes mellitus.

A Cross-Sectional Study of Compositional and Functional Profiles of Gut Microbiota in Sardinian Centenarians

Sardinia, Italy, has a high prevalence of residents who live more than 100 years. The reasons for longevity in this isolated region are currently unknown. Gut microbiota may hold a clue. To explore the role gut microbiota may play in healthy aging and longevity, we used metagenomic sequencing to determine the compositional and functional differences in gut microbiota associated with populations of different ages in Sardinia. Our data revealed that the gut microbiota of both young and elderly Sardinians shared similar taxonomic and functional profiles. A different pattern was found in centenarians. Within the centenarian group, the gut microbiota was correlated with the functional independence measurement of the host. Centenarians had a higher diversity of core microbiota species and microbial genes than those in the young and elderly. We found that the gut microbiota in Sardinian centenarians displayed a rearranged taxonomic pattern compared with those of the young and elderly, featured by depletion of Faecalibacterium prausnitzii and Eubacterium rectale and enriched for Methanobrevibacter smithii and Bifidobacterium adolescentis Moreover, functional analysis revealed that the microbiota in centenarians had high capacity for central metabolism, especially glycolysis and fermentation to short-chain fatty acids (SCFAs), although the gut microbiota in centenarians was low in genes encoding enzymes involved in degradation of carbohydrates, including fibers and galactose.IMPORTANCE The gut microbiota has been proposed as a promising determinant for human health. Centenarians as a model for extreme aging may help us understand the correlation of gut microbiota with healthy aging and longevity. Here we confirmed that centenarians had microbiota elements usually associated with benefits to health. Our finding of a high capacity of glycolysis and related SCFA production represented a healthy microbiome and environment that is regarded as beneficial for host gut epithelium. The low abundance of genes encoding components of pathways involved in carbohydrate degradation was also found in the gut microbiota of Sardinian centenarians and is often associated with poor gut health. Overall, our study here represents an expansion of previous research investigating the age-related changes in gut microbiota. Furthermore, our study provides a new prospective for potential targets for gut microbiota intervention directed at limiting gut inflammation and pathology and enhancing a healthy gut barrier.

Employing toxin-antitoxin genome markers for identification of Bifidobacterium and Lactobacillus strains in human metagenomes

Recent research has indicated that in addition to the unique genotype each individual may also have a unique microbiota composition. Difference in microbiota composition may emerge from both its species and strain constituents. It is important to know the precise composition especially for the gut microbiota (GM), since it can contribute to the health assessment, personalized treatment, and disease prevention for individuals and groups (cohorts). The existing methods for species and strain composition in microbiota are not always precise and usually not so easy to use. Probiotic bacteria of the genus Bifidobacterium and Lactobacillus make an essential component of human GM. Previously we have shown that in certain Bifidobacterium and Lactobacillus species the RelBE and MazEF superfamily of toxin-antitoxin (TA) systems may be used as functional biomarkers to differentiate these groups of bacteria at the species and strain levels. We have composed a database of TA genes of these superfamily specific for all lactobacilli and bifidobacteria species with complete genome sequence and confirmed that in all Lactobacillus and Bifidobacterium species TA gene composition is species and strain specific. To analyze composition of species and strains of two bacteria genera, Bifidobacterium and Lactobacillus, in human GM we developed TAGMA (toxin antitoxin genes for metagenomes analyses) software based on polymorphism in TA genes. TAGMA was tested on gut metagenomic samples. The results of our analysis have shown that TAGMA can be used to characterize species and strains of Lactobacillus and Bifidobacterium in metagenomes.

Biodiversity and dynamics of cyanobacterial communities during blooms in temperate lake (Harsha Lake, Ohio, USA)

Cyanobacterial blooms are intensifying global ecological hazards. The fine structure and dynamics of bloom community are critical to understanding bloom development but little understood. Here, the questions whether dominant bloomers have high diversity and whether dominant OTUs (operational taxonomical units) compete with one another were addressed. 16S rRNA gene amplicons from an annual bloom at five locations in Harsha Lake (Ohio, USA) showed cyanobacteria were the dominant phylum, and co-existing major bacterial phyla included Proteobacteria, Bacteroidetes, Actinoacteria, and Verrucomicrobia. On the genus level, the initial dominance by Dolichospermum in June yielded to Planktothrix in July, which were replaced by Microcystis and Cylindrospermopsis in August throughout the bloom. Based on the number of verified unique OTUs (a within-genus biodiversity metric), dominant genera tended to have high within-genus diversity. For example, Dolichospermum had 57 unique OTUs, Planktothrix had 36, Microcystis had 12, and Cylindrospermopsis had 4 unique OTUs. Interestingly, these different OTUs showed different dynamics and association with other OTUs. First, no between-OTU competitions were observed during the bloom cycle, and dominant OTUs were abundant throughout the bloom. Such biodiversity of OTUs and their dynamics were verified in Microcystis aeruginosa with two microcystin synthetase genes (mcyA and mcyG): the relative abundance of both genes varied during the bloom based on quantitative PCR. Two Dolichospermum circinale OTUs and one P. rubescens OTU were most abundant and persistently present throughout the entire bloom. Second, these OTUs differed in the OTUs they were associated with. Third, these OTUs tended to have different levels of association with the environmental factors, even they belonged to the same genera. These findings suggest the structure and dynamics of a cyanobacterial bloom community is complex, with only few OTUs dominating the bloom. Thus, high-resolution molecular characterization will be necessary to understand bloom development.

Dietary wood pulp-derived sterols modulation of cholesterol metabolism and gut microbiota in high-fat-diet-fed hamsters

Wood pulp-derived sterols (WS) supplementation ameliorated HFD-associated metabolic disorder; WS supplementation increased the amounts of fecal sterols excretion and SCFAs content; WS supplementation modulated gut microbiota composition.

One Health, Fermented Foods, and Gut Microbiota

Changes in present-day society such as diets with more sugar, salt, and saturated fat, bad habits and unhealthy lifestyles contribute to the likelihood of the involvement of the microbiota in inflammatory diseases, which contribute to global epidemics of obesity, depression, and mental health concerns. The microbiota is presently one of the hottest areas of scientific and medical research, and exerts a marked influence on the host during homeostasis and disease. Fermented foods and beverages are generally defined as products made by microbial organisms and enzymatic conversions of major and minor food components. Further to the commonly-recognized effects of nutrition on the digestive health (e.g., dysbiosis) and well-being, there is now strong evidence for the impact of fermented foods and beverages (e.g., yoghurt, pickles, bread, kefir, beers, wines, mead), produced or preserved by the action of microorganisms, on general health, namely their significance on the gut microbiota balance and brain functionality. Fermented products require microorganisms, i.e., Saccharomyces yeasts and lactic acid bacteria, yielding alcohol and lactic acid. Ingestion of vibrant probiotics, especially those contained in fermented foods, is found to cause significant positive improvements in balancing intestinal permeability and barrier function. Our guts control and deal with every aspect of our health. How we digest our food and even the food sensitivities we have is linked with our mood, behavior, energy, weight, food cravings, hormone balance, immunity, and overall wellness. We highlight some impacts in this domain and debate calls for the convergence of interdisciplinary research fields from the United Nations’ initiative. Worldwide human and animal medicine are practiced separately; veterinary science and animal health are generally neither considered nor inserted within national or international Health discussions. The absence of a clear definition and subsequent vision for the future of One Health may act as a barrier to transdisciplinary collaboration. The point of this mini review is to highlight the role of fermented foods and beverages on gut microbiota and debate if the need for confluence of transdisciplinary fields of One Health is feasible and achievable, since they are managed by separate sectors with limited communication.

The Human Microbiota and Obesity: A Literature Systematic Review of In Vivo Models and Technical Approaches

Obesity is a noncommunicable disease that affects a considerable part of humanity. Recently, it has been recognized that gut microbiota constitutes a fundamental factor in the triggering and development of a large number of pathologies, among which obesity is one of the most related to the processes of dysbiosis. In this review, different animal model approaches, methodologies, and genome scale metabolic databases were revisited to study the gut microbiota and its relationship with metabolic disease. As a data source, PubMed for English-language published material from 1 January 2013, to 22 August 2018, were screened. Some previous studies were included if they were considered classics or highly relevant. Studies that included innovative technical approaches or different in vivo or in vitro models for the study of the relationship between gut microbiota and obesity were selected after a 16-different-keyword exhaustive search. A clear panorama of the current available options for the study of microbiota’s influence on obesity, both for animal model election and technical approaches, is presented to the researcher. All the knowledge generated from the study of the microbiota opens the possibility of considering fecal transplantation as a relevant therapeutic alternative for obesity and other metabolic disease treatment.

Mannan-oligosaccharide modulates the obesity and gut microbiota in high-fat diet-fed mice

The gut microbiota is considered to be associated with high-fat diet (HFD)-induced obesity and metabolic syndrome (MS). Mannan-oligosaccharide (MOS) is widely used as a natural additive, and its effect on promoting fat metabolism has been reported. Here, we performed a 11-week study on C57BL/6J mice fed a high-fat diet (HFD) with/without MOS supplementation, and the results showed that MOS could attenuate high-fat diet induced metabolic syndrome, including slower body weight gain, lowered serum lipids and reduced insulin resistance. Next generation sequencing (NGS) of the gut microbiota indicated that MOS modulated the overall structure of the gut microbiome, which was highly correlated with MS parameters. Specifically, the intake of MOS decreased the Firmicutes/Bacteroidetes ratio and could reverse the changes in the relative abundance of several species caused by HFD, including Akkermansia muciniphila, Bacteroides acidifaciens, Lactobacillus gasseri and Bifidobacterium pseudolongum. Thus, MOS has the potential to be used as a new prebiotic for regulating the gut microbiota and helping in attenuating metabolic disorders.

Prebiotics for Lactose Intolerance: Variability in Galacto-Oligosaccharide Utilization by Intestinal Lactobacillus rhamnosus

Lactose intolerance, characterized by a decrease in host lactase expression, affects approximately 75% of the world population. Galacto-oligosaccharides (GOS) are prebiotics that have been shown to alleviate symptoms of lactose intolerance and to modulate the intestinal microbiota, promoting the growth of beneficial microorganisms. We hypothesized that mechanisms of GOS utilization by intestinal bacteria are variable, impacting efficacy and response, with differences occurring at the strain level. This study aimed to determine the mechanisms by which human-derived Lactobacillus rhamnosus strains metabolize GOS. Genomic comparisons between strains revealed differences in carbohydrate utilization components, including transporters, enzymes for degradation, and transcriptional regulation, despite a high overall sequence identity (>95%) between strains. Physiological and transcriptomics analyses showed distinct differences in carbohydrate metabolism profiles and GOS utilization between strains. A putative operon responsible for GOS utilization was identified and characterized by genetic disruption of the 6-phospho-β-galactosidase, which had a critical role in GOS utilization. Our findings highlight the importance of strain-specific bacterial metabolism in the selection of probiotics and synbiotics to alleviate symptoms of gastrointestinal disorders including lactose intolerance.

The Roles of 27 Genera of Human Gut Microbiota in Ischemic Heart Disease, Type 2 Diabetes Mellitus, and Their Risk Factors: A Mendelian Randomization Study

Manipulation of the gut microbiota presents a new opportunity to combat chronic diseases. Randomized controlled trials of probiotics suggest some associations with adiposity, lipids, and insulin resistance, but to our knowledge no trials with "hard" outcomes have been conducted. We used separate-sample Mendelian randomization to obtain estimates of the associations of 27 genera of gut microbiota with ischemic heart disease, type 2 diabetes mellitus, adiposity, lipid levels, and insulin resistance, based on summary data from CARDIoGRAAMplusC4D and other consortia. Among the 27 genera, a 1-allele increase in single nucleotide polymorphisms related to greater abundance of Bifidobacterium was associated with lower risk of ischemic heart disease (odds ratio = 0.985, 95% confidence interval (CI): 0.971, 1.000; P = 0.04), a 0.011-standard-deviation lower body mass index (95% CI: -0.017, -0.005), and a 0.026-standard-deviation higher low-density lipoprotein cholesterol level (95% CI: 0.019, 0.033), but the findings were not robust to exclusion of potential pleiotropy. We also identified Acidaminococcus, Aggregatibacter, Anaerostipes, Blautia, Desulfovibrio, Dorea, and Faecalibacterium as being nominally associated with type 2 diabetes mellitus or other risk factors. Results from our study indicate that these 8 genera of gut microbiota should be given priority in future research relating the gut microbiome to ischemic heart disease and its risk factors.

Effects of fermented milk treatment on microbial population and metabolomic outcomes in a three-stage semi-continuous culture system

We investigated the impact of a fermented milk product on gut microbiota and their metabolism in 3 different conditions of the colon with a systemic viewpoint. An in vitro semi-continuous anaerobic cultivation was used to assess the colon compartment-specific influence of fermented milk, followed by a multiomics approach combining 16S rDNA amplicon sequencing and nuclear magnetic resonance (NMR) spectroscopy. The microbiome profiling and metabolomic features were significantly different across three colon compartments and after fermented milk treatment. Integrative correlation analysis indicated that the alteration of butyrate-producing microbiota (Veillonella, Roseburia, Lachnospira, and Coprococcus) and some primary metabolites (butyrate, ethanol, lactate, and isobutyrate) in the treatment group had a strong association with the fermented milk microorganisms. Our findings suggested that fermented milk treatment significantly affected microbial population in an in vitro cultivation system as well as the colonic metabolome in different ways in each of colon compartment.

The Effect of Lean-Seafood and Non-Seafood Diets on Fecal Metabolites and Gut Microbiome: Results from a Randomized Crossover Intervention Study

SCOPE

The impact of dietary protein types on the gut microbiome is scarcely studied. The aim of the present study is therefore to examine the effects of lean-seafood and non-seafood proteins on the gut microbiome composition and activity and elucidate potential associations to cardiovascular disease (CVD) risk factors.

METHODS

A crossover intervention study in which 20 healthy subjects consumed two diets that varied in protein source was conducted. ¹ H NMR spectroscopy and 16S rDNA sequencing analyses were applied to characterize fecal metabolites and gut microbiota composition, respectively.

RESULTS

A twofold increase in fecal trimethylamine excretion was observed after the lean-seafood diet period. Circulating TAG and the total to high-density lipoprotein (HDL) cholesterol ratio as well as circulating TMAO levels were each associated with specific gut bacteria. Following the non-seafood diet period, a decreased relative abundance of Clostridium cluster IV and a tendency toward an increased Firmicutes/Bacteroidetes ratio were found.

CONCLUSIONS

Lean-seafood and non-seafood diets differentially modulate the gut microbiome composition and activity. Furthermore, the gut microbiota composition seems to affect circulating TMAO levels and CVD risk factors.

Microbiota inoculum composition affects holobiont assembly and host growth in Daphnia

BACKGROUND

Host-associated microbiota is often acquired by horizontal transmission of microbes present in the environment. It is hypothesized that differences in the environmental pool of colonizers can influence microbiota community assembly on the host and as such affect holobiont composition and host fitness. To investigate this hypothesis, the host-associated microbiota of the invertebrate eco(toxico)logical model Daphnia was experimentally disturbed using different concentrations of the antibiotic oxytetracycline. The community assembly and host-microbiota interactions when Daphnia were colonized by the disturbed microbiota were investigated by inoculating germ-free individuals with the microbiota.

RESULTS

Antibiotic-induced disturbance of the microbiota had a strong effect on the subsequent colonization of Daphnia by affecting ecological interactions between members of the microbiota. This resulted in differences in community assembly which, in turn, affected Daphnia growth.

CONCLUSIONS

These results show that the composition of the pool of colonizing microbiota can be an important structuring factor of the microbiota assembly on Daphnia, affecting holobiont composition and host growth. These findings contribute to a better understanding of how the microbial environment can shape the holobiont composition and affect host-microbiota interactions.