Rethinking "enterotypes"

MiDAS 4: A global catalogue of full-length 16S rRNA gene sequences and taxonomy for studies of bacterial communities in wastewater treatment plants

Microbial communities are responsible for biological wastewater treatment, but our knowledge of their diversity and function is still poor. Here, we sequence more than 5 million high-quality, full-length 16S rRNA gene sequences from 740 wastewater treatment plants (WWTPs) across the world and use the sequences to construct the ‘MiDAS 4’ database. MiDAS 4 is an amplicon sequence variant resolved, full-length 16S rRNA gene reference database with a comprehensive taxonomy from domain to species level for all sequences. We use an independent dataset (269 WWTPs) to show that MiDAS 4, compared to commonly used universal reference databases, provides a better coverage for WWTP bacteria and an improved rate of genus and species level classification. Taking advantage of MiDAS 4, we carry out an amplicon-based, global-scale microbial community profiling of activated sludge plants using two common sets of primers targeting regions of the 16S rRNA gene, revealing how environmental conditions and biogeography shape the activated sludge microbiota. We also identify core and conditionally rare or abundant taxa, encompassing 966 genera and 1530 species that represent approximately 80% and 50% of the accumulated read abundance, respectively. Finally, we show that for well-studied functional guilds, such as nitrifiers or polyphosphate-accumulating organisms, the same genera are prevalent worldwide, with only a few abundant species in each genus.

Microbial communities are responsible for biological wastewater treatment. Here, Dueholm et al. generate more than 5 million high-quality, full-length 16S rRNA gene sequences from wastewater treatment plants across the world to construct a database with a comprehensive taxonomy, providing insights into diversity and function of these microbial communities.

Distinctive Microbiome Type Distribution in a Young Adult Balinese Cohort May Reflect Environmental Changes Associated with Modernization

An important public health question is understanding how changes in human environments can drive changes in the gut microbiota that influence risks associated with human health and wellbeing. It is well-documented that the modernization of societies is strongly correlated with intergenerational change in the frequency of nutrition-related chronic diseases in which microbial dysbiosis is implicated. The population of Bali, Indonesia, is well-positioned to study the interconnection between a changing food environment and microbiome patterns in its early stages, because of a recent history of modernization. Here, we characterize the fecal microbiota and diet history of the young adult women in Bali, Indonesia (n = 41) in order to compare microbial patterns in this generation with those of other populations with different histories of a modern food environment (industrialized supply chain). We found strong support for two distinct fecal microbiota community types in our study cohort at similar frequency: a Prevotella-rich (Type-P) and a Bacteroides-rich (Type-B) community (p < 0.001, analysis of similarity, Wilcoxon test). Although Type-P individuals had lower alpha diversity (p < 0.001, Shannon) and higher incidence of obesity, multivariate analyses with diet data showed that community types significantly influenced associations with BMI. In a multi-country dataset (n = 257), we confirmed that microbial beta diversity across subsistent and industrial populations was significantly associated with Prevotella and Bacteroides abundance (p < 0.001, generalized additive model) and that the prevalence of community types differs between societies. The young adult Balinese microbiota was distinctive in having an equal prevalence of two community types. Collectively, our study showed that the incorporation of community types as an explanatory factor into study design or modeling improved the ability to identify microbiome associations with diet and health metrics.

LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

Background

Identification of biomarkers, which are measurable characteristics of biological datasets, can be challenging. Although amplicon sequence variants (ASVs) can be considered potential biomarkers, identifying important ASVs in high-throughput sequencing datasets is challenging. Noise, algorithmic failures to account for specific distributional properties, and feature interactions can complicate the discovery of ASV biomarkers. In addition, these issues can impact the replicability of various models and elevate false-discovery rates. Contemporary machine learning approaches can be leveraged to address these issues. Ensembles of decision trees are particularly effective at classifying the types of data commonly generated in high-throughput sequencing (HTS) studies due to their robustness when the number of features in the training data is orders of magnitude larger than the number of samples. In addition, when combined with appropriate model introspection algorithms, machine learning algorithms can also be used to discover and select potential biomarkers. However, the construction of these models could introduce various biases which potentially obfuscate feature discovery.

Results

We developed a decision tree ensemble, LANDMark, which uses oblique and non-linear cuts at each node. In synthetic and toy tests LANDMark consistently ranked as the best classifier and often outperformed the Random Forest classifier. When trained on the full metabarcoding dataset obtained from Canada’s Wood Buffalo National Park, LANDMark was able to create highly predictive models and achieved an overall balanced accuracy score of 0.96 ± 0.06. The use of recursive feature elimination did not impact LANDMark’s generalization performance and, when trained on data from the BE amplicon, it was able to outperform the Linear Support Vector Machine, Logistic Regression models, and Stochastic Gradient Descent models (p ≤ 0.05). Finally, LANDMark distinguishes itself due to its ability to learn smoother non-linear decision boundaries.

Conclusions

Our work introduces LANDMark, a meta-classifier which blends the characteristics of several machine learning models into a decision tree and ensemble learning framework. To our knowledge, this is the first study to apply this type of ensemble approach to amplicon sequencing data and we have shown that analyzing these datasets using LANDMark can produce highly predictive and consistent models.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04631-z.

Intestinal microbiota signatures of clinical response and immune-related adverse events in melanoma patients treated with anti-PD-1

Ample evidence indicates that the gut microbiome is a tumor-extrinsic factor associated with antitumor response to anti-programmed cell death protein-1 (PD-1) therapy, but inconsistencies exist between published microbial signatures associated with clinical outcomes. To resolve this, we evaluated a new melanoma cohort, along with four published datasets. Time-to-event analysis showed that baseline microbiota composition was optimally associated with clinical outcome at approximately 1 year after initiation of treatment. Meta-analysis and other bioinformatic analyses of the combined data show that bacteria associated with favorable response are confined within the Actinobacteria phylum and the Lachnospiraceae/Ruminococcaceae families of Firmicutes. Conversely, Gram-negative bacteria were associated with an inflammatory host intestinal gene signature, increased blood neutrophil-to-lymphocyte ratio, and unfavorable outcome. Two microbial signatures, enriched for Lachnospiraceae spp. and Streptococcaceae spp., were associated with favorable and unfavorable clinical response, respectively, and with distinct immune-related adverse effects. Despite between-cohort heterogeneity, optimized all-minus-one supervised learning algorithms trained on batch-corrected microbiome data consistently predicted outcomes to programmed cell death protein-1 therapy in all cohorts. Gut microbial communities (microbiotypes) with nonuniform geographical distribution were associated with favorable and unfavorable outcomes, contributing to discrepancies between cohorts. Our findings shed new light on the complex interaction between the gut microbiome and response to cancer immunotherapy, providing a roadmap for future studies.

Colorectal Cancer-Associated Microbiome Patterns and Signatures

The gut microbiome is dynamic and shaped by diet, age, geography, and environment. The disruption of normal gut microbiota (dysbiosis) is closely related to colorectal cancer (CRC) risk and progression. To better identify and characterize CRC-associated dysbiosis, we collected six independent cohorts with matched normal pairs (when available) for comparison and exploration of the microbiota and their interactions with the host. Comparing the microbial community compositions between cancerous and adjacent noncancerous tissues, we found that more microbes were depleted than enriched in tumors. Despite taxonomic variations among cohorts, consistent depletion of normal microbiota (members of Clostridia and Bacteroidia) and significant enrichment of oral-originated pathogens (such as Fusobacterium nucleatum and Parvimonas micra) were observed in CRC compared to normal tissues. Sets of hub and hub-connecting microbes were subsequently identified to infer microbe-microbe interaction networks in CRC. Furthermore, biclustering was used for identifying coherent patterns between patients and microbes. Two patient-microbe interaction patterns, named P0 and P1, can be consistently identified among the investigated six CRC cohorts. Characterization of the microbial community composition of the two patterns revealed that patients in P0 and P1 differed significantly in microbial alpha and beta diversity, and CRC‐associated microbiota changes consist of continuous populations of widespread taxa rather than discrete enterotypes. In contrast to the P0, the patients in P1 have reduced microbial alpha diversity compared to the adjacent normal tissues, and P1 possesses more oral-related pathogens than P0 and controls. Collectively, our study investigated the CRC-associated microbiome changes, and identified reproducible microbial signatures across multiple independent cohorts. More importantly, we revealed that the CRC heterogeneity can be partially attributed to the variety and compositional differences of microbes and their interactions to humans.

Exploring the universal healthy human gut microbiota around the World

The human gut holds a special place in the study of different microbial environments due to growing evidence that the gut microbiota is related to host health. However, despite extensive research, there is still a lack of knowledge about the core taxa forming the gut microbiota and, moreover, available information is biased towards western microbiomes in both genome databases and most core taxa studies. To tackle these limitations, we tested a database enrichment strategy and analyzed public datasets of whole-genome shotgun data, generated from 545 fecal samples, comprising three gradients of westernization. The NT database was selected as a baseline of biological diversity, subsequently being combined with various studies of interest related to the human microbiota. This enrichment strategy made it possible to improve classification capacity, compared to the original unenriched database, regarding the various lifestyles and populations studied. The effects of incomplete-taxonomy metagenome-assembled genomes on genome database enrichment were also examined, revealing that, while they are helpful, they should be used with caution depending on the taxonomic level of interest. Moreover, in terms of high prevalence, the core analysis revealed a conserved set of bacterial taxa in the healthy human gut microbiota worldwide, despite apparent lifestyle differences. Such taxa show a set of traits, metabolic roles, and ancestral status, making them suitable candidates for a hypothetical phylogenetic core of mutualistic microorganisms co-evolving with the human species.

Characterization of the Gut Microbiota in Individuals with Overweight or Obesity during a Real-World Weight Loss Dietary Program: A Focus on the Bacteroides 2 Enterotype

Background: Dietary intervention is a cornerstone of weight loss therapies. In obesity, a dysbiotic gut microbiota (GM) is characterized by high levels of Bacteroides lineages and low diversity. We examined the GM composition changes, including the Bacteroides 2 enterotype (Bact2), in a real-world weight loss study in subjects following a high-protein hypocaloric diet with or without a live microorganisms (LMP) supplement. Method: 263 volunteers were part of this real-world weight loss program. The first phase was a high-protein low-carbohydrate calorie restriction diet with or without LMP supplements. Fecal samples were obtained at baseline and after 10% weight loss for 163 subjects. Metagenomic profiling was obtained by shotgun sequencing. Results: At baseline, the Bact2 enterotype was more prevalent in subjects with aggravated obesity and metabolic alterations. After weight loss, diversity increased and Bact2 prevalence decreased in subjects with lower GM diversity at baseline, notably in LMP consumers. Significant increases in Akkermansia muciniphila and Parabacteroides distasonis and significant decreases of Eubacterium rectale, Streptococcus thermophilus and Bifidobacterial lineages were observed after weight loss. Conclusions: Baseline microbiome composition is associated with differential changes in GM diversity and Bact2 enterotype prevalence after weight loss. Examining these signatures could drive future personalized nutrition efforts towards more favorable microbiome compositions.

Application of Clustering Method to Explore the Correlation Between Dominant Flora and the Autism Spectrum Disorder Clinical Phenotype in Chinese Children

Autism spectrum disorder (ASD) is characterized by deficits in social interactions and repetitive, stereotypic behaviors. Evidence shows that bidirectional communication of the gut-brain axis plays an important role. Here, we recruited 62 patients with ASD in southern China, and performed a cross-sectional study to test the relationship between repeated behavior, gut microbiome composition, and alpha diversity. We divided all participants into two groups based on the clustering results of their microbial compositions and found Veillonella and Ruminococcus as the seed genera in each group. Repetitive behavior differed between clusters, and cluster 2 had milder repetitive symptoms than Cluster 1. Alpha diversity between clusters was significantly different, indicating that cluster 1 had lower alpha diversity and more severe repetitive, stereotypic behaviors. Repetitive behavior had a negative correlation with alpha diversity. We demonstrated that the difference in intestinal microbiome composition and altered alpha diversity can be associated with repetitive, stereotypic behavior in autism. The role of Ruminococcus and Veillonella in ASD is not yet understood.

A Possible Perspective about the Compositional Models, Evolution, and Clinical Meaning of Human Enterotypes

Among the various parameters obtainable through the analysis of the human gut microbiota, the enterotype is one of the first classifications of the bacterial consortia, which tried to obtain, at the same time, as much information as possible to be applied in clinical medicine. Although some authors observed the existence not of clusters, but only of a real continuous gradient, enterotypes are commonly described according to various models. The first model predicted either clustering into enterotypes 1 and 2 based on two specific dominances, Bacteroides and Prevotella, respectively, with the Ruminococcus dominance blurred within the Bacteroides dominance, or it predicted a threedominant condition, in which the Ruminococcus driver constituted enterotype 3, separated from enterotype 1. A second model envisaged three possible ways to cluster gut microbiota, respectively centred on two, three, and four dominances. In the first case, enterotypes 1 and 2 coincided with the two original enterotypes, with the dominance of Bacteroides and Prevotella, respectively. In the second case, the existence of enterotype 3 was evident and whose dominance was not centred on Ruminococcus but extended more towards the entire Firmicutes phylum. In the third case, the presence of the phylum Firmicutes was split into two different enterotypes generating the clusters defined and named as Mixtures 1 and 2. Subsequently, the analysis of the water content (hydration) in the stool allowed the splitting of the Bacteroides enterotype into two sub-enterotype, respectively known as B1 and B2. All these models have allowed us to highlight some correlations between a specific enterotype, or cluster, and some characteristics, such as the greater predisposition of the respective hosts towards certain pathologies. These observations, coupled with the attempt to derive the different microbiota on an evolutionary basis, can help to shed new light on this topic and demonstrate the possible utility that the different ways of clustering the gut microbiota can have in a clinical application perspective and in preventive medicine.

Microbiome Clusters Disclose Physiologic Variances in Dairy Cows Challenged by Calving and Lipopolysaccharides

Dairy cows respond individually to stressful situations, even under similar feeding and housing conditions. The phenotypic responsiveness might trace back to their microbiome and its interactions with the host. This long-term study investigated the effects of calving, lipopolysaccharide (LPS)-induced inflammation, and l-carnitine supplementation on fecal bacteria and metabolites, dairy cow milk production, health, energy metabolism, and blood metabolites. Fifty-four multiparous Holstein dairy cows were examined over a defined period of life (168 days). The obtained data allowed a holistic analysis combining microbiome data such as 16S rRNA amplicon sequencing and fecal targeted metabolome (188 metabolites) with host parameters. The conducted analyses allowed the definition of three enterotype-like microbiome clusters in dairy cows which could be linked to the community diversity and dynamics over time. The microbiome clusters were discovered to be treatment independent, governed by Bifidobacterium (C-Bifi), unclassified (uncl.) Clostridiales (C-Clos), and unclassified Spirochaetaceae (C-Spiro). Animals between the clusters varied significantly in terms of illnesses, body weight, microbiome composition, and milk and blood parameters. C-Bifi animals were healthier and leaner with a less diverse but dynamic microbiome. C-Spiro animals were heavier, but the diversity of the static microbiome was higher. This pioneering study uncovered microbiome clusters in dairy cows, each contributing differently to animal health and productive performance and with a crucial role of Bifidobacterium. IMPORTANCE The health of dairy cows has to be carefully considered for sustainable and efficient animal production. The microbiome of animals plays an important role in the host's nutrient supply and regulation of immune functions. We show that a certain composition of the fecal microbiome, called microbiome clusters, can be linked to an animal's health at challenging life events such as calving and inflammation. Cows with a specific set of bacteria have coped better under these stressors than have others. This novel information has great potential for implementing microbiome clusters as a trait for sustainable breeding strategies.

A macroecological description of alternative stable states reproduces intra- and inter-host variability of gut microbiome

The most fundamental questions in microbial ecology concern the diversity and variability of communities. Their composition varies widely across space and time, as a result of a nontrivial combination of stochastic and deterministic processes. The interplay between nonlinear community dynamics and environmental fluctuations determines the rich statistical structure of community variability. We analyze long time series of individual human gut microbiomes and compare intra- and intercommunity dissimilarity under a macroecological framework. We show that most taxa have large but stationary fluctuations over time, while a minority of taxa display rapid changes in average abundance that cluster in time, suggesting the presence of alternative stable states. We disentangle interindividual variability in a stochastic component and a deterministic one, the latter recapitulated by differences in carrying capacities. Last, by combining environmental fluctuations and alternative stable states, we introduce a model that quantitatively predicts the statistical properties of both intra- and interindividual community variability, therefore summarizing variation in a unique macroecological framework.

Characterizing Enterotypes in Human Metagenomics: A Viral Perspective

The diversity and high genomic mutation rates of viral species hinder our understanding of viruses and their contributions to human health. Viral enterotypes as a description of the gut virome, its characteristics have not been thoroughly studied. Here we investigated the human gut virome composition using previously published sequencing data of 2,690 metagenomes from seven countries with various phenotypes. We found that the virome was dominated by double-stranded DNA viruses in our data, and young children and adults showed different stages in their fecal enterovirus composition. Beta diversity showed there were significantly less homogeneous in individuals with severe disorders of bile acid secretion, such as cirrhosis. In contrast, there were no significant differences in distances to centroids or viral components between patients with phenotypes unrelated to bile acid, such as hypertension. Enterotypes determined independently from various projects showed similar specific viruses and enrichment direction. Confounding factors, such as different sequencing platforms and library construction, did not confuse enterotyping. The gut virome composition pattern could be described by two viral enterotypes, which supported a discrete, rather than a gradient, distribution. Three main components, enterotype 1 and 2 specific viruses and the other, comprise the total viral variation in these sets. Compared with enterotype 2, enterotype 1 had a higher viral count, Shannon index, and similarity between samples. The relative abundance of enterotype-specific viruses is a crucial determinant of enterotype assignment. Samples not matching any of the defined enterotypes in the database did not necessarily correlate to sickness. Therefore, the background context must be carefully considered when using a viral enterotype as a feature for disease prediction. Our results highlight important insights into the human gut virome composition by exploring two-main viral enterotypes in population and providing an alternate covariate for early disease screening.

Ecological and Evolutionary responses to Antibiotic Treatment in the Human Gut Microbiota

The potential for antibiotics to affect the ecology and evolution of the human gut microbiota is well recognised and has wide-ranging implications for host health. Here, we review the findings of key studies that surveyed the human gut microbiota during antibiotic treatment. We find several broad patterns including the loss of diversity, disturbance of community composition, suppression of bacteria in the Actinobacteria phylum, amplification of bacteria in the Bacteroidetes phylum, and promotion of antibiotic resistance. Such changes to the microbiota were often, but not always, recovered following the end of treatment. However, many studies reported unique and/or contradictory results, which highlights our inability to meaningfully predict or explain the effects of antibiotic treatment on the human gut microbiome. This problem arises from variation between existing studies in three major categories: differences in dose, class and combinations of antibiotic treatments used; differences in demographics, lifestyles, and locations of subjects; and differences in measurements, analyses and reporting styles used by researchers. To overcome this, we suggest two integrated approaches: (i) a top-down approach focused on building predictive models through large sample sizes, deep metagenomic sequencing, and effective collaboration; and (ii) a bottom-up reductionist approach focused on testing hypotheses using model systems.

Deterministic transition of enterotypes shapes the infant gut microbiome at an early age

BACKGROUND

The succession of the gut microbiota during the first few years plays a vital role in human development. We elucidate the characteristics and alternations of the infant gut microbiota to better understand the correlation between infant health and microbiota maturation.

RESULTS

We collect 13,776 fecal samples or datasets from 1956 infants between 1 and 3 years of age, based on multi-population cohorts covering 17 countries. The characteristics of the gut microbiota are analyzed based on enterotype and an ecological model. Clinical information (n = 2287) is integrated to understand outcomes of different developmental patterns. Infants whose gut microbiota are dominated by Firmicutes and Bifidobacterium exhibit typical characteristics of early developmental stages, such as unstable community structure and low microbiome maturation, while those driven by Bacteroides and Prevotella are characterized by higher diversity and stronger connections in the gut microbial community. We further reveal a geography-related pattern in global populations. Through ecological modeling and functional analysis, we demonstrate that the transition of the gut microbiota from infants towards adults follows a deterministic pattern; as infants grow up, the dominance of Firmicutes and Bifidobacterium is replaced by that of Bacteroides and Prevotella, along with shifts in specific metabolic pathways.

CONCLUSIONS

By leveraging the extremely large datasets and enterotype-based microbiome analysis, we decipher the colonization and transition of the gut microbiota in infants from a new perspective. We further introduce an ecological model to estimate the tendency of enterotype transitions, and demonstrated that the transition of infant gut microbiota was deterministic and predictable.

New Approaches to Profile the Microbiome for Treatment of Neurodegenerative Disease

Progressive neurodegenerative diseases represent some of the largest growing treatment challenges for public health in modern society. These diseases mainly progress due to aging and are driven by microglial surveillance and activation in response to changes occurring in the aging brain. The lack of efficacious treatment options for Alzheimer's disease (AD), as the focus of this review, and other neurodegenerative disorders has encouraged new approaches to address neuroinflammation for potential treatments. Here we will focus on the increasing evidence that dysbiosis of the gut microbiome is characterized by inflammation that may carry over to the central nervous system and into the brain. Neuroinflammation is the common thread associated with neurodegenerative diseases, but it is yet unknown at what point and how innate immune function turns pathogenic for an individual. This review will address extensive efforts to identify constituents of the gut microbiome and their neuroactive metabolites as a peripheral path to treatment. This approach is still in its infancy in substantive clinical trials and requires thorough human studies to elucidate the metabolic microbiome profile to design appropriate treatment strategies for early stages of neurodegenerative disease. We view that in order to address neurodegenerative mechanisms of the gut, microbiome and metabolite profiles must be determined to pre-screen AD subjects prior to the design of specific, chronic titrations of gut microbiota with low-dose antibiotics. This represents an exciting treatment strategy designed to balance inflammatory microglial involvement in disease progression with an individual's manifestation of AD as influenced by a coercive inflammatory gut.

Effect of Diet and Dietary Components on the Composition of the Gut Microbiota

Diet and dietary components have profound effects on the composition of the gut microbiota and are among the most important contributors to the alteration in bacterial flora. This review examines the effects the "Western", "plant-based", "high-fat", "medical ketogenic", and "Mediterranean" diets have on the composition of the gut microbiota in both mice and human subjects. We show that specific dietary components that are commonly found in the "plant-based" and "Mediterranean" diet play a role in shifting the microbial composition. This review further evaluates the bacterial metabolites that are associated with diet, and their role in systemic inflammation and metabolic endotoxemia. Furthermore, the associations between diet/dietary components and altering bacterial composition, may lead to potential therapeutic targets for type II diabetes, obesity, and inflammatory diseases.

Two community types occur in gut microbiota of large-sample wild plateau pikas (Ochotona curzoniae)

Studies on large-sample gut microbial sequencing data indicate that gut microbiota can be divided into multiple community types; different community types may influence the community function and ecosystem service. However, the knowledge on the classification, diversity, interaction, and assembling of microbial community types in the gut of wild animals is still insufficient. Here, we used pika gut microbiota data as an example to study the microbial community types in large-sample sequencing dataset. Cecal microbial communities from 118 wild plateau pika (Ochotona curzoniae) individuals at 5 elevational regions on the Qinghai-Tibet Plateau were analyzed. Our results show that pika gut microbiota can be separated into 2 community types (Cluster I and Cluster II). Cluster I was mainly distributed on the high-elevation regions with more than 3694 m and was most dominated by Firmicutes. Cluster II was from the low-elevation areas (lower than 3580 m), and was predominated by Bacteroidetes. Cluster I had a higher community alpha-diversity and predicted functional diversity than Cluster II, and the beta-diversity and predicted functional profiles of these 2 clusters were significantly different. Network analysis revealed that there were more complex interactions between Cluster I, which had enhanced influence on the co-occurrences of other microbes in the bacterial community when compared to Cluster II. Phylogenetic analysis found that the environmental filtering in the Cluster I was stronger than Cluster II. The assemblages of pika gut bacterial communities were determined mainly by deterministic processes, while the relative importance of deterministic processes accounted for more percentages in the Cluster I than Cluster II. Our results demonstrated that 2 gut microbial community types in pikas had distinct diversity patterns and ecological functions. Current methods are also helpful for identifying gut community types and the related mechanisms behind gut microbiota types in large-sample sequencing data of wild animals.

Gut microbiota changes after metabolic surgery in adult diabetic patients with mild obesity: a randomised controlled trial

BACKGROUND

Roux-en-Y gastric bypass (RYGB) surgery is one of the most efficient procedures for the treatment of obesity, also improving metabolic and inflammatory status, in patients with mild obesity. The underlying mechanisms have not been fully understood, but gut microbiota is hypothesized to play a key role. Our aim was to evaluate the association between gut microbiota changes and anthropometric, metabolic and inflammatory profiles after metabolic surgery compared with medical therapy, in type 2 diabetic (T2DM) adults with mild obesity (BMI 30-35 kg/m²).

METHODS

DM² was an open-label, randomised controlled clinical trial (RCT: ISRCTN53984585) with 2 arms: (i) surgical, and (ii) medical. The main outcome was gut microbiota changes after: metabolic surgery (Roux-en-Y gastric bypass-RYGB) versus standard medical therapy. Secondary outcomes included anthropometric, metabolic and inflammatory profiles. Clinical visits, blood workup, and stool samples were collected at baseline and months (M)1, 3, 6, 12. Gut microbiota was profiled using 16S rRNA targeted sequencing.

RESULTS

Twenty patients were included: 10 in surgical and 10 in medical arm. Anthropometric and metabolic comparative analysis favoured RYGB over medical arm. At M12, the percentage of weight loss was 25.5 vs. 4.9% (p < 0.001) and HbA1c was 6.2 vs. 7.7% (p < 0.001) respectively. We observed a continuous increase of genus richness after RYGB up until M12. In the medical arm, genus richness ended-up being significantly lower at M12. Composition analysis indicated significant changes of the overall microbial ecosystem (permanova p = 0.004, [R² = 0.17]) during the follow-up period after RYGB. There was a strong association between improvement of anthropometric/metabolic/inflammatory biomarkers and increase in microbial richness and Proteobacterial lineages.

CONCLUSIONS

This was the first RCT studying composite clinical, analytic, and microbiome changes in T2DM patients with class 1 obesity after RYGB versus standard medical therapy. The remarkable phenotypic improvement after surgery occurred concomitantly with changes in the gut microbiome, but at a lower level.

TRIAL REGISTRATION

ISRCTN53984585.

Gene-level metagenomic architectures across diseases yield high-resolution microbiome diagnostic indicators

We propose microbiome disease “architectures”: linking >1 million microbial features (species, pathways, and genes) to 7 host phenotypes from 13 cohorts using a pipeline designed to identify associations that are robust to analytical model choice. Here, we quantify conservation and heterogeneity in microbiome-disease associations, using gene-level analysis to identify strain-specific, cross-disease, positive and negative associations. We find coronary artery disease, inflammatory bowel diseases, and liver cirrhosis to share gene-level signatures ascribed to the Streptococcus genus. Type 2 diabetes, by comparison, has a distinct metagenomic signature not linked to any one specific species or genus. We additionally find that at the species-level, the prior-reported connection between Solobacterium moorei and colorectal cancer is not consistently identified across models—however, our gene-level analysis unveils a group of robust, strain-specific gene associations. Finally, we validate our findings regarding colorectal cancer and inflammatory bowel diseases in independent cohorts and identify that features inversely associated with disease tend to be less reproducible than features enriched in disease. Overall, our work is not only a step towards gene-based, cross-disease microbiome diagnostic indicators, but it also illuminates the nuances of the genetic architecture of the human microbiome, including tension between gene- and species-level associations.

Here, combing the massive gene-universe of the gut microbiome to identify strain-specific, cross-disease, associations across seven human diseases, the authors introduce the concept of microbiome architecture, defined as the complete set of positive and negative associations between microbial genes and human host disease, highlighting microbiome architectures as potential diagnostic indicators.

Dietary Strategies for Management of Metabolic Syndrome: Role of Gut Microbiota Metabolites

Metabolic syndrome (MetS) is a complex pathophysiological state with incidence similar to that of a global epidemic and represents a risk factor for the onset of chronic non-communicable degenerative diseases (NCDDs), including cardiovascular disease (CVD), type 2 diabetes mellitus, chronic kidney disease, and some types of cancer. A plethora of literature data suggest the potential role of gut microbiota in interfering with the host metabolism, thus influencing several MetS risk factors. Perturbation of the gut microbiota’s composition and activity, a condition known as dysbiosis, is involved in the etiopathogenesis of multiple chronic diseases. Recent studies have shown that some micro-organism-derived metabolites (including trimethylamine N-oxide (TMAO), lipopolysaccharide (LPS) of Gram-negative bacteria, indoxyl sulfate and p-cresol sulfate) induce subclinical inflammatory processes involved in MetS. Gut microbiota’s taxonomic species or abundance are modified by many factors, including diet, lifestyle and medications. The main purpose of this review is to highlight the correlation between different dietary strategies and changes in gut microbiota metabolites. We mainly focus on the validity/inadequacy of specific dietary patterns to reduce inflammatory processes, including leaky gut and subsequent endotoxemia. We also describe the chance of probiotic supplementation to interact with the immune system and limit negative consequences associated with MetS.

Diet and gut microbiome enterotype are associated at the population level in African buffalo

Studies in humans and laboratory animals link stable gut microbiome “enterotypes” with long-term diet and host health. Understanding how this paradigm manifests in wild herbivores could provide a mechanistic explanation of the relationships between microbiome dynamics, changes in dietary resources, and outcomes for host health. We identify two putative enterotypes in the African buffalo gut microbiome. The enterotype prevalent under resource-abundant dietary regimes, regardless of environmental conditions, has high richness, low between- and within-host beta diversity, and enrichment of genus Ruminococcaceae-UCG-005. The second enterotype, prevalent under restricted dietary conditions, has reduced richness, elevated beta diversity, and enrichment of genus Solibacillus. Population-level gamma diversity is maintained during resource restriction by increased beta diversity between individuals, suggesting a mechanism for population-level microbiome resilience. We identify three pathogens associated with microbiome variation depending on host diet, indicating that nutritional background may impact microbiome-pathogen dynamics. Overall, this study reveals diet-driven enterotype plasticity, illustrates ecological processes that maintain microbiome diversity, and identifies potential associations between diet, enterotype, and disease.

There are stable relationships between diet and microbiome in humans and lab animals. A study on African buffalo finds that diet influences microbiome variation and enterotype formation. Three pathogens may associate with microbiome depending on host diet, suggesting nutrition impacts relationships between gut microbiome and host health.

Associations between habitual diet, metabolic disease, and the gut microbiota using latent Dirichlet allocation

BACKGROUND

The gut microbiome impacts human health through various mechanisms and is involved in the development of a range of non-communicable diseases. Diet is a well-known factor influencing microbe-host interaction in health and disease. However, very few findings are based on large-scale analysis using population-based studies. Our aim was to investigate the cross-sectional relationship between habitual dietary intake and gut microbiota structure in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 study.

RESULTS

Fecal microbiota was analyzed using 16S rRNA gene amplicon sequencing. Latent Dirichlet allocation (LDA) was applied to samples from 1992 participants to identify 20 microbial subgroups within the study population. Each participant's gut microbiota was subsequently described by a unique composition of these 20 subgroups. Associations between habitual dietary intake, assessed via repeated 24-h food lists and a Food Frequency Questionnaire, and the 20 subgroups, as well as between prevalence of metabolic diseases/risk factors and the subgroups, were assessed with multivariate-adjusted Dirichlet regression models. After adjustment for multiple testing, eight of 20 microbial subgroups were significantly associated with habitual diet, while nine of 20 microbial subgroups were associated with the prevalence of one or more metabolic diseases/risk factors. Subgroups 5 (Faecalibacterium, Lachnospiracea incertae sedis, Gemmiger, Roseburia) and 14 (Coprococcus, Bacteroides, Faecalibacterium, Ruminococcus) were particularly strongly associated with diet. For example, participants with a high probability for subgroup 5 were characterized by a higher Alternate Healthy Eating Index and Mediterranean Diet Score and a higher intake of food items such as fruits, vegetables, legumes, and whole grains, while participants with prevalent type 2 diabetes mellitus were characterized by a lower probability for subgroup 5.

CONCLUSIONS

The associations between habitual diet, metabolic diseases, and microbial subgroups identified in this analysis not only expand upon current knowledge of diet-microbiota-disease relationships, but also indicate the possibility of certain microbial groups to be modulated by dietary intervention, with the potential of impacting human health. Additionally, LDA appears to be a powerful tool for interpreting latent structures of the human gut microbiota. However, the subgroups and associations observed in this analysis need to be replicated in further studies. Video abstract.

A genome-wide association study for gut metagenome in Chinese adults illuminates complex diseases

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 <20% genetic contribution to the gut microbiota. Using common variants-, rare variants-, and copy number variations-based association analyses, we identified abundant signals associated with the gut microbiome especially in metabolic, neurological, and immunological functions. The controversial concept of enterotypes may have a genetic attribute, with the top two loci explaining 11% of the 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.

Impact of Microbial Metabolites on Microbiota-Gut-Brain Axis in Inflammatory Bowel Disease

The complex bidirectional communication system existing between the gastrointestinal tract and the brain initially termed the "gut-brain axis" and renamed the "microbiota-gut-brain axis", considering the pivotal role of gut microbiota in sustaining local and systemic homeostasis, has a fundamental role in the pathogenesis of Inflammatory Bowel Disease (IBD). The integration of signals deriving from the host neuronal, immune, and endocrine systems with signals deriving from the microbiota may influence the development of the local inflammatory injury and impacts also more distal brain regions, underlying the psychophysiological vulnerability of IBD patients. Mood disorders and increased response to stress are frequently associated with IBD and may affect the disease recurrence and severity, thus requiring an appropriate therapeutic approach in addition to conventional anti-inflammatory treatments. This review highlights the more recent evidence suggesting that alterations of the microbiota-gut-brain bidirectional communication axis may concur to IBD pathogenesis and sustain the development of both local and CNS symptoms. The participation of the main microbial-derived metabolites, also defined as "postbiotics", such as bile acids, short-chain fatty acids, and tryptophan metabolites in the development of IBD-associated gut and brain dysfunction will be discussed. The last section covers a critical evaluation of the main clinical evidence pointing to the microbiome-based therapeutic approaches for the treatment of IBD-related gastrointestinal and neuropsychiatric symptoms.

Introduction to host microbiome symbiosis in health and disease

Humans share a core intestinal microbiome and yet human microbiome differs by genes, species, enterotypes (ecology), and gene count (microbial diversity). Achievement of microbiota metagenomic analysis has revealed that the microbiome gene count is a key stratifier of health in several immune disorders and clinical conditions. We review here the progress of the metagenomic pipeline analysis, and how this has allowed us to define the host-microbe symbiosis associated with a healthy status. The link between host-microbe symbiosis disruption, the so-called dysbiosis and chronic diseases or iatrogenic conditions is highlighted. Finally, opportunities to use microbiota modulation, with specific nutrients and/or live microbes, as a target for personalized nutrition and therapy for the maintenance, preservation, or restoration of host-microbe symbiosis are discussed.

Association Between Gut Akkermansia and Metabolic Syndrome is Dose-Dependent and Affected by Microbial Interactions: A Cross-Sectional Study

OBJECTIVE

Akkermansia muciniphila is among the most abundant bacterial species in the human intestine; however, its relationship to metabolic syndrome (MetS)-which is linked to gut dysbiosis-is not known. In this study, we investigated the association between Akkermansia abundance and risk of MetS and its components, as well as dose-response effects and the influence of microbial interactions on the association.

METHODS

This cross-sectional study included 6896 Chinese participants aged 18 to 97 years from the Guangdong Gut Microbiome Project. MetS was defined according to Joint Committee for Developing Chinese Guidelines on Prevention and Treatment of Dyslipidemia in Adults criteria. The abundance of Akkermansia was assessed by 16S rRNA sequencing. Logistic regression analysis with adjustment for common confounders was performed to evaluate the association between Akkermansia and MetS and its components. Models with restricted cubic splines and interaction terms were used to examine the dose-response association and microbial interactions, respectively.

RESULTS

The prevalence of MetS was 20.4%, and the median abundance of Akkermansia was 0.08% (interquartile range: 0.04-0.93%). Increased Akkermansia abundance was associated with decreased risk of MetS (P _nonlinear<0.05), but this effect was not observed until the Akkermansia level was 0.2% of the total gut microbiota abundance (odds ratio=0.96, 95% confidence interval: 0.94-0.98). Of the 5 MetS components, obesity and hypertriglyceridemia showed the strongest association with Akkermansia, followed by reduced high-density lipoprotein cholesterol, hypertension, and hyperglycemia. Microbial interaction analyses showed that Ruminococcaceae and Lachnospiraceae were the predominant bacterial families and were not only correlated with Akkermansia abundance but also influenced the Akkermansia-MetS association.

CONCLUSION

There is a dose-response association between reduced risk of MetS and increased abundance of Akkermansia. The association between Akkermansia and 5 MetS components is variable and affected by microbial interactions.

Emotional well-being and gut microbiome profiles by enterotype

With increasing attention being paid to improving emotional well-being, recent evidence points to gut microbiota as a key player in regulating mental and physical health via bidirectional communication between the brain and gut. Here, we examine the association between emotional well-being and gut microbiome profiles (i.e., gut microbiome composition, diversity, and the moderating role of the enterotypes) among healthy Korean adults (n = 83, mean age = 48.9, SD = 13.2). The research was performed using high-throughput 16S rRNA gene sequencing to obtain gut microbiome profiles, as well as a self-report survey that included the Positive Affect Negative Affect Schedule (PANAS). The cluster-based analysis identified two enterotypes dominated by the genera Bacteroides (n = 49) and Prevotella (n = 34). Generalized linear regression analysis reveals significant associations between positive emotion and gut microbiome diversity (Shannon Index) among participants in the Prevotella dominant group, whereas no such relationship emerged among participants in the Bacteroides group. Moreover, a novel genus from the family Lachnospiraceae is associated with emotional well-being scores, both positive and negative. Together, the current findings highlight the enterotype-specific links between the gut microbiota community and emotion in healthy adults and suggest the possible roles of the gut microbiome in promoting mental health.

Association between the body weight of growing pigs and the functional capacity of their gut microbiota

Gastrointestinal microbiota impact host's biological activities, including digestion of indigestible feed components, energy harvest, and immunity. In this study, fecal microbiota of high body weight (HW) and low body weight (LW) growing pigs at 103 days of age were compared. Principal coordinates analysis separated the HW and LW groups into two clusters, indicating their potential differences between microbial community composition. Although the abundances of two major phyla, Firmicutes and Bacteroidetes, did not significantly differ between the HW and LW groups, some genera showed significant differences. Among them, Peptococcus and Eubacterium exhibited strong positive correlations with body weight (BW) and average daily gain (ADG) (Rho > 0.40), whereas Treponema, Desulfovibrio, Parabacteroides, and Ruminococcaceae_unclassified exhibited strong negative correlations with BW and ADG (Rho < -0.40). Based on these results, the structure of intestinal microbiota may affect growth traits in pigs through host-microbe interactions. Further in-depth studies will provide insights into how best to reshape host-microbe interactions in pigs and other animals as well.

Initial Sequencing and Characterization of the Gastrointestinal and Oral Microbiota in Urban Pakistani Adults

We report the initial characterization of the gastrointestinal tract (gut) and oral microbiota (bacteria) in 32 urban Pakistani adults. Study participants were between ages 18 and 40, had body mass index between 18 and 25 Kg/m², and were students or early-career professionals. These individuals donated a total of 61 samples (32 gut and 29 oral) that were subjected to 16S ribosomal RNA (rRNA) gene sequencing. Microbiome composition of Pakistani individuals was compared against the uBiome database of selected individuals who self-reported to be in excellent health. We observed strong gender-based differences in the gut microbiome of Pakistani individuals, a skewness toward Firmicutes, and unusually high levels of Proteobacteria in the Pakistani men. These observations may indicate microbiota dysbiosis, though 16S data alone can neither establish cause nor effect to human health. Albeit conducted on a smaller scale, our report provides a first snapshot about the composition and diversity of gut and oral microbiota communities in Pakistani individuals.

B cell superantigens in the human intestinal microbiota

IgA is prominently secreted at mucosal surfaces and coats a fraction of the commensal microbiota, a process that is critical for intestinal homeostasis. However, the mechanisms of IgA induction and the molecular targets of these antibodies remain poorly understood, particularly in humans. Here, we demonstrate that microbiota from a subset of human individuals encode two protein "superantigens" expressed on the surface of commensal bacteria of the family Lachnospiraceae such as Ruminococcus gnavus that bind IgA variable regions and stimulate potent IgA responses in mice. These superantigens stimulate B cells expressing human VH3 or murine VH5/6/7 variable regions and subsequently bind their antibodies, allowing these microbial organisms to become highly coated with IgA in vivo. These findings demonstrate a previously unappreciated role for commensal superantigens in host-microbiota interactions. Furthermore, as superantigen-expressing strains show an uneven distribution across human populations, they should be systematically considered in studies evaluating human B cell responses and microbiota during homeostasis and disease.

Does an Apple a Day Also Keep the Microbes Away? The Interplay Between Diet, Microbiota, and Host Defense Peptides at the Intestinal Mucosal Barrier

A crucial mechanism of intestinal defense includes the production and secretion of host defense peptides (HDPs). HDPs control pathogens and commensals at the intestinal interface by direct killing, by sequestering vital ions, or by causing bacterial cells to aggregate in the mucus layer. Accordingly, the combined activity of various HDPs neutralizes gut bacteria before reaching the mucosa and thus helps to maintain the homeostatic balance between the host and its microbes at the mucosal barrier. Defects in the mucosal barrier have been associated with various diseases that are on the rise in the Western world. These include metabolic diseases, such as obesity and type 2 diabetes, and inflammatory intestinal disorders, including ulcerative colitis and Crohn's disease, the two major entities of inflammatory bowel disease. While the etiology of these diseases is multifactorial, highly processed Western-style diet (WSD) that is rich in carbohydrates and fat and low in dietary fiber content, is considered to be a contributing lifestyle factor. As such, WSD does not only profoundly affect the resident microbes in the intestine, but can also directly alter HDP function, thereby potentially contributing to intestinal mucosal barrier dysfunction. In this review we aim to decipher the complex interaction between diet, microbiota, and HDPs. We discuss how HDP expression can be modulated by specific microbes and their metabolites as well as by dietary factors, including fibers, lipids, polyphenols and vitamins. We identify several dietary compounds that lead to reduced HDP function, but also factors that stimulate HDP production in the intestine. Furthermore, we argue that the effect of HDPs against commensal bacteria has been understudied when compared to pathogens, and that local environmental conditions also need to be considered. In addition, we discuss the known molecular mechanisms behind HDP modulation. We believe that a better understanding of the diet-microbiota-HDP interdependence will provide insights into factors underlying modern diseases and will help to identify potential dietary interventions or probiotic supplementation that can promote HDP-mediated intestinal barrier function in the Western gut.

Does the Gut Microbiota Modulate Host Physiology through Polymicrobial Biofilms?

Microbes inhabit various environments, such as soil, water environments, plants, and animals. Humans harbor a complex commensal microbial community in the gastrointestinal tract, which is known as the gut microbiota. The gut microbiota participates not only in various metabolic processes in the human body, it also plays a critical role in host immune responses. Gut microbes that inhabit the intestinal epithelial surface form polymicrobial biofilms. In the last decade, it has been widely reported that gut microbial biofilms and gut microbiota-derived products, such as metabolites and bacterial membrane vesicles, not only directly affect the host intestinal environment, but also indirectly influence the health of the host. In this review, we discuss the most recent findings from human and animal studies on the interactions between the gut microbiota and hosts, and their associations with various disorders, including inflammatory diseases, atopic dermatitis, metabolic disorders, and psychiatric and neurological diseases. The integrated approach of metabologenomics together with biofilm imaging may provide valuable insights into the gut microbiota and suggest remedies that may lead to a healthier society.

The Effects of Nutrition on the Gastrointestinal Microbiome of Cats and Dogs: Impact on Health and Disease

The gastrointestinal (GI) microbiome of cats and dogs is increasingly recognized as a metabolically active organ inextricably linked to pet health. Food serves as a substrate for the GI microbiome of cats and dogs and plays a significant role in defining the composition and metabolism of the GI microbiome. The microbiome, in turn, facilitates the host's nutrient digestion and the production of postbiotics, which are bacterially derived compounds that can influence pet health. Consequently, pet owners have a role in shaping the microbiome of cats and dogs through the food they choose to provide. Yet, a clear understanding of the impact these food choices have on the microbiome, and thus on the overall health of the pet, is lacking. Pet foods are formulated to contain the typical nutritional building blocks of carbohydrates, proteins, and fats, but increasingly include microbiome-targeted ingredients, such as prebiotics and probiotics. Each of these categories, as well as their relative proportions in food, can affect the composition and/or function of the microbiome. Accumulating evidence suggests that dietary components may impact not only GI disease, but also allergies, oral health, weight management, diabetes, and kidney disease through changes in the GI microbiome. Until recently, the focus of microbiome research was to characterize alterations in microbiome composition in disease states, while less research effort has been devoted to understanding how changes in nutrition can influence pet health by modifying the microbiome function. This review summarizes the impact of pet food nutritional components on the composition and function of the microbiome and examines evidence for the role of nutrition in impacting host health through the microbiome in a variety of disease states. Understanding how nutrition can modulate GI microbiome composition and function may reveal new avenues for enhancing the health and resilience of cats and dogs.

Revealing links between gut microbiome and its fungal community in Type 2 Diabetes Mellitus among Emirati subjects: A pilot study

Type 2 diabetes mellitus (T2DM) drastically affects the population of Middle East countries with an ever-increasing number of overweight and obese individuals. The precise links between T2DM and gut microbiome composition remain elusive in these populations. Here, we performed 16 S rRNA and ITS2- gene based microbial profiling of 50 stool samples from Emirati adults with or without T2DM. The four major enterotypes initially described in westernized cohorts were retrieved in this Emirati population. T2DM and non-T2DM healthy controls had different microbiome compositions, with an enrichment in Prevotella enterotype in non-T2DM controls whereas T2DM individuals had a higher proportion of the dysbiotic Bacteroides 2 enterotype. No significant differences in microbial diversity were observed in T2DM individuals after controlling for cofounding factors, contrasting with reports from westernized cohorts. Interestingly, fungal diversity was significantly decreased in Bacteroides 2 enterotype. Functional profiling from 16 S rRNA gene data showed marked differences between T2DM and non-T2DM controls, with an enrichment in amino acid degradation and LPS-related modules in T2DM individuals, whereas non-T2DM controls had increased abundance of carbohydrate degradation modules in concordance with enterotype composition. These differences provide an insight into gut microbiome composition in Emirati population and its potential role in the development of diabetes mellitus.

Longitudinal analysis reveals transition barriers between dominant ecological states in the gut microbiome

Deep molecular phenotyping of individuals provides the opportunity for biological insight into host physiology. As the human microbiome is increasingly being recognized as an important determinant of host health, understanding the host–microbiome relationship in a multiomics context may pave the way forward for targeted interventions. In this study, we analyze gut microbial composition of 101 individuals over the course of a year, alongside clinical markers and serum metabolomics. We establish association between specific gut compositional states and host health biomarkers (e.g., of inflammation). Finally, we provide evidence for an apparent transition barrier between these compositional states. A deeper understanding of microbiome dynamics and the associated variation in host phenotypes furthers our ability to engineer effective interventions that optimize wellness.

The Pioneer 100 Wellness Project involved quantitatively profiling 108 participants’ molecular physiology over time, including genomes, gut microbiomes, blood metabolomes, blood proteomes, clinical chemistries, and data from wearable devices. Here, we present a longitudinal analysis focused specifically around the Pioneer 100 gut microbiomes. We distinguished a subpopulation of individuals with reduced gut diversity, elevated relative abundance of the genus Prevotella, and reduced levels of the genus Bacteroides. We found that the relative abundances of Bacteroides and Prevotella were significantly correlated with certain serum metabolites, including omega-6 fatty acids. Primary dimensions in distance-based redundancy analysis of clinical chemistries explained 18.5% of the variance in bacterial community composition, and revealed a Bacteroides/Prevotella dichotomy aligned with inflammation and dietary markers. Finally, longitudinal analysis of gut microbiome dynamics within individuals showed that direct transitions between Bacteroides-dominated and Prevotella-dominated communities were rare, suggesting the presence of a barrier between these states. One implication is that interventions seeking to transition between Bacteroides- and Prevotella-dominated communities will need to identify permissible paths through ecological state-space that circumvent this apparent barrier.

The athletic gut microbiota

The microorganisms in the gastrointestinal tract play a significant role in nutrient uptake, vitamin synthesis, energy harvest, inflammatory modulation, and host immune response, collectively contributing to human health. Important factors such as age, birth method, antibiotic use, and diet have been established as formative factors that shape the gut microbiota. Yet, less described is the role that exercise plays, particularly how associated factors and stressors, such as sport/exercise-specific diet, environment, and their interactions, may influence the gut microbiota. In particular, high-level athletes offer remarkable physiology and metabolism (including muscular strength/power, aerobic capacity, energy expenditure, and heat production) compared to sedentary individuals, and provide unique insight in gut microbiota research. In addition, the gut microbiota with its ability to harvest energy, modulate the immune system, and influence gastrointestinal health, likely plays an important role in athlete health, wellbeing, and sports performance. Therefore, understanding the mechanisms in which the gut microbiota could play in the role of influencing athletic performance is of considerable interest to athletes who work to improve their results in competition as well as reduce recovery time during training. Ultimately this research is expected to extend beyond athletics as understanding optimal fitness has applications for overall health and wellness in larger communities. Therefore, the purpose of this narrative review is to summarize current knowledge of the athletic gut microbiota and the factors that shape it. Exercise, associated dietary factors, and the athletic classification promote a more “health-associated” gut microbiota. Such features include a higher abundance of health-promoting bacterial species, increased microbial diversity, functional metabolic capacity, and microbial-associated metabolites, stimulation of bacterial abundance that can modulate mucosal immunity, and improved gastrointestinal barrier function.

Understanding the microbiome: a primer on the role of the microbiome in colorectal neoplasia

Colorectal cancer is a leading cause of cancer-related death internationally, with mounting evidence pointing to the role of the microbiome in adenoma and cancer development. This article aims to provide clinicians with a foundation for understanding the field of research into the microbiome. We also illustrate the various ways in which the microbiota have been linked to colorectal cancer, with a specific focus on microbiota with identified virulence factors, and also on the ways that byproducts of microbiota metabolism may result in oncogenesis. We also review strategies for manipulating the microbiome for therapeutic effects.

The Salivary Mycobiome Contains 2 Ecologically Distinct Mycotypes

A broad range of fungi has been detected in molecular surveys of the oral mycobiome. However, knowledge is still lacking on interindividual variability of these communities and the ecologic and clinical significance of oral fungal commensals. In this cross-sectional study, we use internal transcribed spacer 1 amplicon sequencing to evaluate the salivary mycobiome in 59 subjects, 36 of whom were scheduled to receive cancer chemotherapy. Analysis of the broad population structure of fungal communities in the whole cohort identified 2 well-demarcated genus-level community types (mycotypes), with Candida and Malassezia as the main taxa driving cluster partitioning. The Candida mycotype had lower diversity than the Malassezia mycotype and was positively correlated with cancer and steroid use in these subjects, smoking, caries, utilizing a removable prosthesis, and plaque index. Mycotypes were also associated with metabolically distinct bacteria indicative of divergent oral environments, with aciduric species enriched in the Candida mycotype and inflammophilic bacteria increased in the Malassezia mycotype. Similar to their fungal counterparts, coexisting bacterial communities associated with the Candida mycotype showed lower diversity than those associated with the Malassezia mycotype, suggesting that common environmental pressures affected bacteria and fungi. Mycotypes were also seen in an independent cohort of 24 subjects, in which cultivation revealed Malassezia as viable oral mycobiome members, although the low-abundance Malassezia sympodialis was the only Malassezia species recovered. There was a high degree of concordance between the molecular detection and cultivability of Candida, while cultivation showed low sensitivity for detection of the Malassezia mycotype. Overall, our work provides insights into the oral mycobiome landscape, revealing 2 community classes with apparently distinct ecologic constraints and specific associations with coexisting bacteria and clinical parameters. The utility of mycotypes as biomarkers for oral diseases warrants further study.

Microbiotyping the Sinonasal Microbiome

This study offers a novel description of the sinonasal microbiome, through an unsupervised machine learning approach combining dimensionality reduction and clustering. We apply our method to the International Sinonasal Microbiome Study (ISMS) dataset of 410 sinus swab samples. We propose three main sinonasal "microbiotypes" or "states": the first is Corynebacterium-dominated, the second is Staphylococcus-dominated, and the third dominated by the other core genera of the sinonasal microbiome (Streptococcus, Haemophilus, Moraxella, and Pseudomonas). The prevalence of the three microbiotypes studied did not differ between healthy and diseased sinuses, but differences in their distribution were evident based on geography. We also describe a potential reciprocal relationship between Corynebacterium species and Staphylococcus aureus, suggesting that a certain microbial equilibrium between various players is reached in the sinuses. We validate our approach by applying it to a separate 16S rRNA gene sequence dataset of 97 sinus swabs from a different patient cohort. Sinonasal microbiotyping may prove useful in reducing the complexity of describing sinonasal microbiota. It may drive future studies aimed at modeling microbial interactions in the sinuses and in doing so may facilitate the development of a tailored patient-specific approach to the treatment of sinus disease in the future.

Intestinal microbiome analysis demonstrates azithromycin post-treatment effects improve when combined with lactulose

BACKGROUND

Next-generation sequencing has revolutionized our perspective on the gut microbiome composition, revealing the true extent of the adverse effects of antibiotics. The impact of antibiotic treatment on gut microbiota must be considered and researched to provide grounds for establishing new treatment strategies that are less devastating on commensal bacteria. This study investigates the impact on gut microbiome when a commonly used antibiotic, azithromycin is administered, as well as uncovers the benefits induced when it is used in combination with lactulose, a prebiotic known to enhance the proliferation of commensal microbes.

METHODS

16S rRNA gene sequencing analysis of stool samples obtained from 87 children treated with azithromycin in combination with or without lactulose have been determined. Children's gut microbial profile was established at the pre- and post-treatment stage.

RESULTS

Azithromycin caused an increase in the relative abundance of opportunistic pathogens such as Streptococcus that was evident 60 days after treatment. While few days after treatment, children who also received lactulose started to show a higher relative abundance of saccharolytic bacteria such as Lactobacillus, Enterococcus, Anaerostipes, Blautia and Roseburia, providing a protective role against opportunistic pathogens. In addition, azithromycin-prebiotic combination was able to provide a phylogenetic profile more similar to the pre-treatment stage.

CONCLUSION

It is suggested that during azithromycin treatment, lactulose is able to reinstate the microbiome equilibrium much faster as it promotes saccharolytic microbes and provides a homeostatic effect that minimizes the opportunistic pathogen colonization.

Linking Human Milk Oligosaccharides, Infant Fecal Community Types, and Later Risk To Require Antibiotics

Human milk is the sole and recommended nutrition for the newborn infant and contains one of the largest constituents of diverse oligosaccharides, dubbed human milk oligosaccharides (HMOs). Preclinical and clinical association studies indicate that HMOs have multiple physiological functions largely mediated through the establishment of the gut microbiome. Until recently, HMOs were not available to investigate their role in randomized controlled intervention trials. To our knowledge, this is the first report on the effects of 2 HMOs on establishing microbiota in newborn infants. We provide a detailed description of the microbiota changes observed upon feeding a formula with 2 HMOs in comparison to breastfed reference infants' microbiota. Then, we associate the microbiota to long-term health as assessed by prescribed antibiotic use.

Human milk oligosaccharides (HMOs) may provide health benefits to infants partly by shaping the development of the early-life intestinal microbiota. In a randomized double-blinded controlled multicentric clinical trial, healthy term infants received either infant formula (control) or the same formula with two HMOs (2′-fucosyllactose and lacto-N-neotetraose; test) from enrollment (0 to 14 days) to 6 months. Then, all infants received the same follow-up formula without HMOs until 12 months of age. Breastfed infants (BF) served as a reference group. Stool microbiota at 3 and 12 months, analyzed by 16S rRNA gene sequencing, clustered into seven fecal community types (FCTs) with marked differences in total microbial abundances. Three of the four 12-month FCTs were likely precursors of the adult enterotypes. At 3 months, microbiota composition in the test group (n = 58) appeared closer to that of BF (n = 35) than control (n = 63) by microbiota alpha (within group) and beta (between groups) diversity analyses and distribution of FCTs. While bifidobacteriaceae dominated two FCTs, its abundance was significantly higher in one (FCT BiH for Bifidobacteriaceae at high abundance) than in the other (FCT Bi for Bifidobacteriaceae). HMO supplementation increased the number of infants with FCT BiH (predominant in BF) at the expense of FCT Bi (predominant in control). We explored the association of the FCTs with reported morbidities and medication use up to 12 months. Formula-fed infants with FCT BiH at 3 months were significantly less likely to require antibiotics during the first year than those with FCT Bi. Previously reported lower rates of infection-related medication use with HMOs may therefore be linked to gut microbiota community types. (This study has been registered at ClinicalTrials.gov under registration number NCT01715246.)

The Human Oral Microbiome in Health and Disease: From Sequences to Ecosystems

Abstract: The human oral cavity is home to an abundant and diverse microbial community (i.e., the oral microbiome), whose composition and roles in health and disease have been the focus of intense research in recent years. Thanks to developments in sequencing-based approaches, such as 16S ribosomal RNA metabarcoding, whole metagenome shotgun sequencing, or meta-transcriptomics, we now can efficiently explore the diversity and roles of oral microbes, even if unculturable. Recent sequencing-based studies have charted oral ecosystems and how they change due to lifestyle or disease conditions. As studies progress, there is increasing evidence of an important role of the oral microbiome in diverse health conditions, which are not limited to diseases of the oral cavity. This, in turn, opens new avenues for microbiome-based diagnostics and therapeutics that benefit from the easy accessibility of the oral cavity for microbiome monitoring and manipulation. Yet, many challenges remain ahead. In this review, we survey the main sequencing-based methodologies that are currently used to explore the oral microbiome and highlight major findings enabled by these approaches. Finally, we discuss future prospects in the field.

Dietary metabolism, the gut microbiome, and heart failure

Advances in our understanding of how the gut microbiota contributes to human health and diseases have expanded our insight into how microbial composition and function affect the human host. Heart failure is associated with splanchnic circulation congestion, leading to bowel wall oedema and impaired intestinal barrier function. This situation is thought to heighten the overall inflammatory state via increased bacterial translocation and the presence of bacterial products in the systemic blood circulation. Several metabolites produced by gut microorganisms from dietary metabolism have been linked to pathologies such as atherosclerosis, hypertension, heart failure, chronic kidney disease, obesity, and type 2 diabetes mellitus. These findings suggest that the gut microbiome functions like an endocrine organ by generating bioactive metabolites that can directly or indirectly affect host physiology. In this Review, we discuss several newly discovered gut microbial metabolic pathways, including the production of trimethylamine and trimethylamine N-oxide, short-chain fatty acids, and secondary bile acids, that seem to participate in the development and progression of cardiovascular diseases, including heart failure. We also discuss the gut microbiome as a novel therapeutic target for the treatment of cardiovascular disease, and potential strategies for targeting intestinal microbial processes.

Using compositional principal component analysis to describe children's gut microbiota in relation to diet and body composition

BACKGROUND

Gut microbiota data obtained by DNA sequencing are complex and compositional because of large numbers of detectable taxa, and because microbiota characteristics are described in relative terms. Nutrition researchers use principal component analysis (PCA) to derive dietary patterns from food data. Although compositional PCA methods are not commonly used to describe patterns from complex microbiota data, this approach would be useful for identifying gut microbiota patterns associated with diet and body composition.

OBJECTIVES

To use compositional PCA to describe the principal components (PCs) of gut microbiota in 5-y-old children and explore associations between microbiota components, diet, and BMI z-score.

METHODS

A fecal sample was provided by 319 children aged 5 y. Their primary caregiver completed a validated 123-item quantitative FFQ. Body composition was determined using DXA, and a BMI z-score was calculated. Compositional PCA identified characterizing taxa and weightings for calculation of gut microbiota PC scores at the genus level, and was examined in relation to diet and body size.

RESULTS

Three gut microbiota PCs were found. PC1 (negative loadings on uncultured Christensenellaceae and Ruminococcaceae) was related to lower BMI z-scores and longer duration of breastfeeding (per month) (β = -0.14; 95% CI: -0.26, -0.02; and β = 0.02; 95% CI: 0.003, 0.34, respectively). PC2 (positive loadings on Fusicatenibacter and Bifidobacterium; negative loadings on Bacteroides) was associated with a lower intake of nuts, seeds, and legumes (β = -0.05 per gram; 95% CI: -0.09, -0.01). When adjusted for fiber intake, PC2 was also associated with higher BMI z-scores (β = 0.12; 95% CI: 0.01, 0.24). PC3 (positive loadings on Faecalibacterium, Eubacterium, and Roseburia) was associated with higher intakes of fiber (β = 0.02 per gram; 95% CI: 0.003, 0.04) and total nonstarch polysaccharides (β = 0.02 per gram; 95% CI: 0.003, 0.04).

CONCLUSIONS

Our results suggest that specific gut microbiota components determined using compositional PCA are associated with diet and BMI z-score.This trial was registered at clinicaltrials.gov as NCT00892983.