A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature. 2012;490:55-60. [PMID: 23023125 DOI: 10.1038/nature11450]

Alteration of the intestinal barrier and GLP2 secretion in Berberine-treated type 2 diabetic rats

For centuries, Berberine has been used in the treatment of enteritis in China, and it is also known to have anti-hyperglycemic effects in type 2 diabetic patients. However, as Berberine is insoluble and rarely absorbed in gastrointestinal tract, the mechanism by which it works is unclear. We hypothesized that it may act locally by ameliorating intestinal barrier abnormalities and endotoxemia. A high-fat diet combined with low-dose streptozotocin was used to induce type 2 diabetes in male Sprague Dawley rats. Berberine (100 mg/kg) was administered by lavage to diabetic rats for 2 weeks and saline was given to controls. Hyperinsulinemia and insulin resistance improved in the Berberine group, although there was no significant decrease in blood glucose. Berberine treatment also led to a notable restoration of intestinal villi/mucosa structure and less infiltration of inflammatory cells, along with a decrease in plasma lipopolysaccharide (LPS) level. Tight junction protein zonula occludens 1 (ZO1) was also decreased in diabetic rats but was restored by Berberine treatment. Glutamine-induced glucagon-like peptide 2 (GLP2) secretion from ileal tissue decreased dramatically in the diabetic group but was restored by Berberine treatment. Fasting insulin, insulin resistance index, plasma LPS level, and ZO1 expression were significantly correlated with GLP2 level. In type 2 diabetic rats, Berberine treatment not only augments GLP2 secretion and improves diabetes but is also effective in repairing the damaged intestinal mucosa, restoring intestinal permeability, and improving endotoxemia. Whether these effects are mechanistically related will require further studies, but they certainly support the hypothesis that Berberine acts via modulation of intestinal function.

Factors that drive variation among gut microbial communities

Surveys of humans from around the world have revealed differences in gut microbiota composition among geographically separated populations. But because humans from the same regions often share common ancestry as well as dietary and cultural habits, most studies have not been able to differentiate among the effects of heritable factors and external factors on the composition of the gut microbiota. Here we discuss how the analysis of gut microbial communities of chimpanzees residing in Gombe Stream National Park has provided an unprecedented opportunity to measure the effects of external factors while controlling for heritable factors. The differences in gut microbiota composition between separated host populations of chimpanzees are due almost entirely to external factors, with the contribution of heritable factors to intraspecific variation in gut microbiota composition being too small to detect. The dominant influence of external factors in generating differences among the gut microbiota of our closest relatives lends promise to the possibility of manipulating the composition of the gut microbiome within human hosts. These results highlight the need for controlled studies that isolate the roles of specific external factors, such as diet, cultural practices and geography, in generating differences in the gut microbiota composition.

Human gut microbiota changes reveal the progression of glucose intolerance

To explore the relationship of gut microbiota with the development of type 2 diabetes (T2DM), we analyzed 121 subjects who were divided into 3 groups based on their glucose intolerance status: normal glucose tolerance (NGT; n = 44), prediabetes (Pre-DM; n = 64), or newly diagnosed T2DM (n = 13). Gut microbiota characterizations were determined with 16S rDNA-based high-throughput sequencing. T2DM-related dysbiosis was observed, including the separation of microbial communities and a change of alpha diversity between the different glucose intolerance statuses. To assess the correlation between metabolic parameters and microbiota diversity, clinical characteristics were also measured and a significant association between metabolic parameters (FPG, CRP) and gut microbiota was found. In addition, a total of 28 operational taxonomic units (OTUs) were found to be related to T2DM status by the Kruskal-Wallis H test, most of which were enriched in the T2DM group. Butyrate-producing bacteria (e.g. Akkermansia muciniphila ATCCBAA-835, and Faecalibacterium prausnitzii L2-6) had a higher abundance in the NGT group than in the pre-DM group. At genus level, the abundance of Bacteroides in the T2DM group was only half that of the NGT and Pre-DM groups. Previously reported T2DM-related markers were also compared with the data in this study, and some inconsistencies were noted. We found that Verrucomicrobiae may be a potential marker of T2DM as it had a significantly lower abundance in both the pre-DM and T2DM groups. In conclusion, this research provides further evidence of the structural modulation of gut microbiota in the pathogenesis of diabetes.

What has high-throughput sequencing ever done for us?

This month's Genome Watch looks back over the past 10 years and highlights how the incredible advances in sequencing technologies have transformed research into microbial genomes.

The gut microbiota and obesity: from correlation to causality

The gut microbiota has been linked with chronic diseases such as obesity in humans. However, the demonstration of causality between constituents of the microbiota and specific diseases remains an important challenge in the field. In this Opinion article, using Koch's postulates as a conceptual framework, I explore the chain of causation from alterations in the gut microbiota, particularly of the endotoxin-producing members, to the development of obesity in both rodents and humans. I then propose a strategy for identifying the causative agents of obesity in the human microbiota through a combination of microbiome-wide association studies, mechanistic analysis of host responses and the reproduction of diseases in gnotobiotic animals.

Towards a predictive systems-level model of the human microbiome: progress, challenges, and opportunities

The human microbiome represents a vastly complex ecosystem that is tightly linked to our development, physiology, and health. Our increased capacity to generate multiple channels of omic data from this system, brought about by recent advances in high throughput molecular technologies, calls for the development of systems-level methods and models that take into account not only the composition of genes and species in a microbiome but also the interactions between these components. Such models should aim to study the microbiome as a community of species whose metabolisms are tightly intertwined with each other and with that of the host, and should be developed with a view towards an integrated, comprehensive, and predictive modeling framework. Here, we review recent work specifically in metabolic modeling of the human microbiome, highlighting both novel methodologies and pressing challenges. We discuss various modeling approaches that lay the foundation for a full-scale predictive model, focusing on models of interactions between microbial species, metagenome-scale models of community-level metabolism, and models of the interaction between the microbiome and the host. Continued development of such models and of their integration into a multi-scale model of the microbiome will lead to a deeper mechanistic understanding of how variation in the microbiome impacts the host, and will promote the discovery of clinically relevant and ecologically relevant insights from the rich trove of data now available.

Dysbiosis signature of fecal microbiota in colorectal cancer patients

The human gut microbiota is a complex system that is essential to the health of the host. Increasing evidence suggests that the gut microbiota may play an important role in the pathogenesis of colorectal cancer (CRC). In this study, we used pyrosequencing of the 16S rRNA gene V3 region to characterize the fecal microbiota of 19 patients with CRC and 20 healthy control subjects. The results revealed striking differences in fecal microbial population patterns between these two groups. Partial least-squares discriminant analysis showed that 17 phylotypes closely related to Bacteroides were enriched in the gut microbiota of CRC patients, whereas nine operational taxonomic units, represented by the butyrate-producing genera Faecalibacterium and Roseburia, were significantly less abundant. A positive correlation was observed between the abundance of Bacteroides species and CRC disease status (R = 0.462, P = 0.046 < 0.5). In addition, 16 genera were significantly more abundant in CRC samples than in controls, including potentially pathogenic Fusobacterium and Campylobacter species at genus level. The dysbiosis of fecal microbiota, characterized by the enrichment of potential pathogens and the decrease in butyrate-producing members, may therefore represent a specific microbial signature of CRC. A greater understanding of the dynamics of the fecal microbiota may assist in the development of novel fecal microbiome-related diagnostic tools for CRC.

Transient flare of ulcerative colitis after fecal microbiota transplantation for recurrent Clostridium difficile infection

Clostridium difficile infection (CDI) is a common cause of infectious diarrhea and is usually treated with metronidazole or vancomycin. CDI recurs in 15%-30% of patients after the initial episode and in up to 65% after a second episode. Recurrent infections are a challenge to treat, and patients are usually managed with prolonged pulsed or tapered vancomycin. Fecal microbiota transplantation is an alternative treatment that has a 91% rate of success worldwide, with no reported complications. We describe a patient with ulcerative colitis that had been quiescent for more than 20 years who developed a flare of ulcerative colitis after fecal microbiota transplantation, indicating the need for caution in treating CDI with fecal microbiota transplantation in patients with inflammatory bowel disease.

Functional profiling of the gut microbiome in disease-associated inflammation

The microbial residents of the human gut are a major factor in the development and lifelong maintenance of health. The gut microbiota differs to a large degree from person to person and has an important influence on health and disease due to its interaction with the human immune system. Its overall composition and microbial ecology have been implicated in many autoimmune diseases, and it represents a particularly important area for translational research as a new target for diagnostics and therapeutics in complex inflammatory conditions. Determining the biomolecular mechanisms by which altered microbial communities contribute to human disease will be an important outcome of current functional studies of the human microbiome. In this review, we discuss functional profiling of the human microbiome using metagenomic and metatranscriptomic approaches, focusing on the implications for inflammatory conditions such as inflammatory bowel disease and rheumatoid arthritis. Common themes in gut microbial ecology have emerged among these diverse diseases, but they have not yet been linked to targetable mechanisms such as microbial gene and genome composition, pathway and transcript activity, and metabolism. Combining these microbial activities with host gene, transcript and metabolic information will be necessary to understand how and why these complex interacting systems are altered in disease-associated inflammation.

Omics approaches to study host-microbiota interactions

The intestinal microbiota has profound effects on our physiology and immune system and disturbances in the equilibrium between microbiota and host have been observed in many disorders. Here we discuss the possibilities to further our understanding of how microbiota impacts on human health and disease through the use of large-scale quantifiable tools such as transcriptomics, metagenomics and metabolomics. Reductionist models, including gnotobiotic mouse models have their place in testing hypotheses and elucidating mechanisms by which specific communities or individual species impact on host biology. Network biology approaches can be combined with studies in animal models and cell lines to create iterative cycle of hypotheses and testing, possibly leading to testing in clinical and nutritional intervention studies.

Metabolic modeling of species interaction in the human microbiome elucidates community-level assembly rules

The human microbiome plays a key role in human health and is associated with numerous diseases. Metagenomic-based studies are now generating valuable information about the composition of the microbiome in health and in disease, demonstrating nonneutral assembly processes and complex co-occurrence patterns. However, the underlying ecological forces that structure the microbiome are still unclear. Specifically, compositional studies alone with no information about mechanisms of interaction, potential competition, or syntrophy, cannot clearly distinguish habitat-filtering and species assortment assembly processes. To address this challenge, we introduce a computational framework, integrating metagenomic-based compositional data with genome-scale metabolic modeling of species interaction. We use in silico metabolic network models to predict levels of competition and complementarity among 154 microbiome species and compare predicted interaction measures to species co-occurrence. Applying this approach to two large-scale datasets describing the composition of the gut microbiome, we find that species tend to co-occur across individuals more frequently with species with which they strongly compete, suggesting that microbiome assembly is dominated by habitat filtering. Moreover, species' partners and excluders exhibit distinct metabolic interaction levels. Importantly, we show that these trends cannot be explained by phylogeny alone and hold across multiple taxonomic levels. Interestingly, controlling for host health does not change the observed patterns, indicating that the axes along which species are filtered are not fully defined by macroecological host states. The approach presented here lays the foundation for a reverse-ecology framework for addressing key questions concerning the assembly of host-associated communities and for informing clinical efforts to manipulate the microbiome.

Beneficial metabolic effects of a probiotic via butyrate-induced GLP-1 hormone secretion

Obesity and diabetes are associated with excess caloric intake and reduced energy expenditure resulting in a negative energy balance. The incidence of diabetes has reached epidemic proportions, and childhood diabetes and obesity are increasing alarmingly. Therefore, it is important to develop safe, easily deliverable, and economically viable treatment alternatives for these diseases. Here, we provide data supporting the candidacy of probiotics as such a therapeutic modality against obesity and diabetes. Probiotics are live bacteria that colonize the gastrointestinal tract and impart beneficial effects for health. However, their widespread prescription as medical therapies is limited primarily because of the paucity of our understanding of their mechanism of action. Here, we demonstrate that the administration of a probiotic, VSL#3, prevented and treated obesity and diabetes in several mouse models. VSL#3 suppressed body weight gain and insulin resistance via modulation of the gut flora composition. VSL#3 promoted the release of the hormone GLP-1, resulting in reduced food intake and improved glucose tolerance. The VSL#3-induced changes were associated with an increase in the levels of a short chain fatty acid (SCFA), butyrate. Using a cell culture system, we demonstrate that butyrate stimulated the release of GLP-1 from intestinal L-cells, thereby providing a plausible mechanism for VSL#3 action. These findings suggest that probiotics such as VSL#3 can modulate the gut microbiota-SCFA-hormone axis. Moreover, our results indicate that probiotics are of potential therapeutic utility to counter obesity and diabetes.

NOD2 prevents emergence of disease-predisposing microbiota

The gut flora is composed of a huge number of diverse, well-adapted symbionts that interact with epithelial lining throughout the host's entire life. Not all commensals have the same ability to maintain quiescent, protective inflammation. Importantly, instability in the composition of gut microbial communities (referred to as dysbiosis) has been linked to loss of gut barrier in the context of common human illnesses with increasing socio-economic impacts, such as Crohn disease and colorectal cancer. Our recent findings suggest that disease-predisposing dysbiosis can now be intentionally manipulated by targeting the major Crohn disease-predisposing NOD2 gene. That knowledge will not only add a new dimension to the often overlooked microbiology of Crohn disease and colorectal cancer, but will also have a broad impact on biomedical sciences worldwide.

Role of the gut microbiota in health and chronic gastrointestinal disease: understanding a hidden metabolic organ

The human gut microbiota has become the subject of extensive research in recent years and our knowledge of the resident species and their potential functional capacity is rapidly growing. Our gut harbours a complex community of over 100 trillion microbial cells which influence human physiology, metabolism, nutrition and immune function while disruption to the gut microbiota has been linked with gastrointestinal conditions such as inflammatory bowel disease and obesity. Here, we review the many significant recent studies that have centred on further enhancing our understanding of the complexity of intestinal communities as well as their genetic and metabolic potential. These have provided important information with respect to what constitutes a 'healthy gut microbiota' while furthering our understanding of the role of gut microbes in intestinal diseases. We also highlight recently developed genomic and other tools that are used to study the gut microbiome and, finally, we consider the manipulation of the gut microbiota as a potential therapeutic option to treat chronic gastrointestinal disease.

Random sampling process leads to overestimation of β-diversity of microbial communities

The site-to-site variability in species composition, known as β-diversity, is crucial to understanding spatiotemporal patterns of species diversity and the mechanisms controlling community composition and structure. However, quantifying β-diversity in microbial ecology using sequencing-based technologies is a great challenge because of a high number of sequencing errors, bias, and poor reproducibility and quantification. Herein, based on general sampling theory, a mathematical framework is first developed for simulating the effects of random sampling processes on quantifying β-diversity when the community size is known or unknown. Also, using an analogous ball example under Poisson sampling with limited sampling efforts, the developed mathematical framework can exactly predict the low reproducibility among technically replicate samples from the same community of a certain species abundance distribution, which provides explicit evidences of random sampling processes as the main factor causing high percentages of technical variations. In addition, the predicted values under Poisson random sampling were highly consistent with the observed low percentages of operational taxonomic unit (OTU) overlap (<30% and <20% for two and three tags, respectively, based on both Jaccard and Bray-Curtis dissimilarity indexes), further supporting the hypothesis that the poor reproducibility among technical replicates is due to the artifacts associated with random sampling processes. Finally, a mathematical framework was developed for predicting sampling efforts to achieve a desired overlap among replicate samples. Our modeling simulations predict that several orders of magnitude more sequencing efforts are needed to achieve desired high technical reproducibility. These results suggest that great caution needs to be taken in quantifying and interpreting β-diversity for microbial community analysis using next-generation sequencing technologies.

Due to the vast diversity and uncultivated status of the majority of microorganisms, microbial detection, characterization, and quantitation are of great challenge. Although large-scale metagenome sequencing technology such as PCR-based amplicon sequencing has revolutionized the studies of microbial communities, it suffers from several inherent drawbacks, such as a high number of sequencing errors, biases, poor quantitation, and very high percentages of technical variations, which could greatly overestimate microbial biodiversity. Based on general sampling theory, this study provided the first explicit evidence to demonstrate the importance of random sampling processes in estimating microbial β-diversity, which has not been adequately recognized and addressed in microbial ecology. Since most ecological studies are involved in random sampling, the conclusions learned from this study should also be applicable to other ecological studies in general. In summary, the results presented in this study should have important implications for examining microbial biodiversity to address both basic theoretical and applied management questions.

The abundance and variety of carbohydrate-active enzymes in the human gut microbiota

Descriptions of the microbial communities that live on and in the human body have progressed at a spectacular rate over the past 5 years, fuelled primarily by highly parallel DNA-sequencing technologies and associated advances in bioinformatics, and by the expectation that understanding how to manipulate the structure and functions of our microbiota will allow us to affect health and prevent or treat diseases. Among the myriad of genes that have been identified in the human gut microbiome, those that encode carbohydrate-active enzymes (CAZymes) are of particular interest, as these enzymes are required to digest most of our complex repertoire of dietary polysaccharides. In this Analysis article, we examine the carbohydrate-digestive capacity of a simplified but representative mini-microbiome in order to highlight the abundance and variety of bacterial CAZymes that are represented in the human gut microbiota.

Colonization resistance and microbial ecophysiology: using gnotobiotic mouse models and single-cell technology to explore the intestinal jungle

The highly diverse intestinal microbiota forms a structured community engaged in constant communication with itself and its host and is characterized by extensive ecological interactions. A key benefit that the microbiota affords its host is its ability to protect against infections in a process termed colonization resistance (CR), which remains insufficiently understood. In this review, we connect basic concepts of CR with new insights from recent years and highlight key technological advances in the field of microbial ecology. We present a selection of statistical and bioinformatics tools used to generate hypotheses about synergistic and antagonistic interactions in microbial ecosystems from metagenomic datasets. We emphasize the importance of experimentally testing these hypotheses and discuss the value of gnotobiotic mouse models for investigating specific aspects related to microbiota-host-pathogen interactions in a well-defined experimental system. We further introduce new developments in the area of single-cell analysis using fluorescence in situ hybridization in combination with metabolic stable isotope labeling technologies for studying the in vivo activities of complex community members. These approaches promise to yield novel insights into the mechanisms of CR and intestinal ecophysiology in general, and give researchers the means to experimentally test hypotheses in vivo at varying levels of biological and ecological complexity.

Integrative analysis of the microbiome and metabolome of the human intestinal mucosal surface reveals exquisite inter-relationships

BACKGROUND

Consistent compositional shifts in the gut microbiota are observed in IBD and other chronic intestinal disorders and may contribute to pathogenesis. The identities of microbial biomolecular mechanisms and metabolic products responsible for disease phenotypes remain to be determined, as do the means by which such microbial functions may be therapeutically modified.

RESULTS

The composition of the microbiota and metabolites in gut microbiome samples in 47 subjects were determined. Samples were obtained by endoscopic mucosal lavage from the cecum and sigmoid colon regions, and each sample was sequenced using the 16S rRNA gene V4 region (Illumina-HiSeq 2000 platform) and assessed by UPLC mass spectroscopy. Spearman correlations were used to identify widespread, statistically significant microbial-metabolite relationships. Metagenomes for identified microbial OTUs were imputed using PICRUSt, and KEGG metabolic pathway modules for imputed genes were assigned using HUMAnN. The resulting metabolic pathway abundances were mostly concordant with metabolite data. Analysis of the metabolome-driven distribution of OTU phylogeny and function revealed clusters of clades that were both metabolically and metagenomically similar.

CONCLUSIONS

The results suggest that microbes are syntropic with mucosal metabolome composition and therefore may be the source of and/or dependent upon gut epithelial metabolites. The consistent relationship between inferred metagenomic function and assayed metabolites suggests that metagenomic composition is predictive to a reasonable degree of microbial community metabolite pools. The finding that certain metabolites strongly correlate with microbial community structure raises the possibility of targeting metabolites for monitoring and/or therapeutically manipulating microbial community function in IBD and other chronic diseases.

The genetics of complex cholestatic disorders

Cholestatic liver diseases are caused by a range of hepatobiliary insults and involve complex interactions among environmental and genetic factors. Little is known about the pathogenic mechanisms of specific cholestatic diseases, which has limited our ability to manage patients with these disorders. However, recent genome-wide studies have provided insight into the pathogenesis of gallstones, primary biliary cirrhosis, and primary sclerosing cholangitis. A lithogenic variant in the gene that encodes the hepatobiliary transporter ABCG8 has been identified as a risk factor for gallstone disease; this variant has been associated with altered cholesterol excretion and metabolism. Other variants of genes encoding transporters that affect the composition of bile have been associated with cholestasis, namely ABCB11, which encodes the bile salt export pump, and ABCB4, which encodes hepatocanalicular phosphatidylcholine floppase. In contrast, studies have associated primary biliary cirrhosis and primary sclerosing cholangitis with genes encoding major histocompatibility complex proteins and identified loci associated with microbial sensing and immune regulatory pathways outside this region, such as genes encoding IL12, STAT4, IRF5, IL2 and its receptor (IL2R), CD28, and CD80. These discoveries have raised interest in the development of reagents that target these gene products. We review recent findings from genetic studies of patients with cholestatic liver disease. Future characterization of genetic variants in animal models, stratification of risk alleles by clinical course, and identification of interacting environmental factors will increase our understanding of these complex cholestatic diseases.

Effector and memory T cell responses to commensal bacteria

Barrier surfaces are home to a vast population of commensal organisms that together encode millions of proteins; each of them possessing several potential foreign antigens. Regulation of immune responses to this enormous antigenic load represents a tremendous challenge for the immune system. Tissues exposed to commensals have developed elaborate systems of regulation including specialized populations of resident lymphocytes that maintain barrier function and limit potential responses to commensal antigens. However, in settings of infection and inflammation these regulatory mechanisms are compromised and specific effector responses against commensal bacteria can develop. This review discusses the circumstances controlling the fate of commensal specific T cells and how dysregulation of these responses could lead to severe pathological outcomes.

High-resolution quantitative metabolome analysis of urine by automated flow injection NMR

Metabolism is essential to understand human health. To characterize human metabolism, a high-resolution read-out of the metabolic status under various physiological conditions, either in health or disease, is needed. Metabolomics offers an unprecedented approach for generating system-specific biochemical definitions of a human phenotype through the capture of a variety of metabolites in a single measurement. The emergence of large cohorts in clinical studies increases the demand of technologies able to analyze a large number of measurements, in an automated fashion, in the most robust way. NMR is an established metabolomics tool for obtaining metabolic phenotypes. Here, we describe the analysis of NMR-based urinary profiles for metabolic studies, challenged to a large human study (3007 samples). This method includes the acquisition of nuclear Overhauser effect spectroscopy one-dimensional and J-resolved two-dimensional (J-Res-2D) ¹H NMR spectra obtained on a 600 MHz spectrometer, equipped with a 120 μL flow probe, coupled to a flow-injection analysis system, in full automation under the control of a sampler manager. Samples were acquired at a throughput of ∼20 (or 40 when J-Res-2D is included) min/sample. The associated technical analysis error over the full series of analysis is 12%, which demonstrates the robustness of the method. With the aim to describe an overall metabolomics workflow, the quantification of 36 metabolites, mainly related to central carbon metabolism and gut microbial host cometabolism, was obtained, as well as multivariate data analysis of the full spectral profiles. The metabolic read-outs generated using our analytical workflow can therefore be considered for further pathway modeling and/or biological interpretation.

Causes, consequences, and perspectives in the variations of intestinal density of colonization of multidrug-resistant enterobacteria

The intestinal microbiota is a complex environment that hosts 10¹³ to 10¹⁴ bacteria. Among these bacteria stand multidrug-resistant enterobacteria (MDRE), which intestinal densities can substantially vary, especially according to antibiotic exposure. The intestinal density of MDRE and their relative abundance (i.e., the proportion between the density of MDRE and the density of total enterobacteria) could play a major role in the infection process or patient-to-patient transmission. This review discusses the recent advances in understanding (i) what causes variations in the density or relative abundance of intestinal colonization, (ii) what are the clinical consequences of these variations, and (iii) what are the perspectives for maintaining these markers at low levels.

Computational meta'omics for microbial community studies

Complex microbial communities are an integral part of the Earth's ecosystem and of our bodies in health and disease. In the last two decades, culture-independent approaches have provided new insights into their structure and function, with the exponentially decreasing cost of high-throughput sequencing resulting in broadly available tools for microbial surveys. However, the field remains far from reaching a technological plateau, as both computational techniques and nucleotide sequencing platforms for microbial genomic and transcriptional content continue to improve. Current microbiome analyses are thus starting to adopt multiple and complementary meta'omic approaches, leading to unprecedented opportunities to comprehensively and accurately characterize microbial communities and their interactions with their environments and hosts. This diversity of available assays, analysis methods, and public data is in turn beginning to enable microbiome-based predictive and modeling tools. We thus review here the technological and computational meta'omics approaches that are already available, those that are under active development, their success in biological discovery, and several outstanding challenges.

Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity

Obesity and type 2 diabetes are characterized by altered gut microbiota, inflammation, and gut barrier disruption. Microbial composition and the mechanisms of interaction with the host that affect gut barrier function during obesity and type 2 diabetes have not been elucidated. We recently isolated Akkermansia muciniphila, which is a mucin-degrading bacterium that resides in the mucus layer. The presence of this bacterium inversely correlates with body weight in rodents and humans. However, the precise physiological roles played by this bacterium during obesity and metabolic disorders are unknown. This study demonstrated that the abundance of A. muciniphila decreased in obese and type 2 diabetic mice. We also observed that prebiotic feeding normalized A. muciniphila abundance, which correlated with an improved metabolic profile. In addition, we demonstrated that A. muciniphila treatment reversed high-fat diet-induced metabolic disorders, including fat-mass gain, metabolic endotoxemia, adipose tissue inflammation, and insulin resistance. A. muciniphila administration increased the intestinal levels of endocannabinoids that control inflammation, the gut barrier, and gut peptide secretion. Finally, we demonstrated that all these effects required viable A. muciniphila because treatment with heat-killed cells did not improve the metabolic profile or the mucus layer thickness. In summary, this study provides substantial insight into the intricate mechanisms of bacterial (i.e., A. muciniphila) regulation of the cross-talk between the host and gut microbiota. These results also provide a rationale for the development of a treatment that uses this human mucus colonizer for the prevention or treatment of obesity and its associated metabolic disorders.

Linking the microbiota and metabolic disease with lymphotoxin

The field of lymphotoxin biology has seen many advances in the past decade. Notably, a role for lymphotoxin as a key effector cytokine has emerged to add to its foundational contribution to lymphoid organogenesis. It is now clear that lymphotoxin contributes to host defense for a wide variety of pathogens, and the lymphotoxin receptor is a defining feature of and regulatory mechanism in both innate and adaptive immunities. Specifically, lymphotoxin contributes to Th education, licensing of IL-22 production from type 3 innate lymphoid cells, and even maintains innate myeloid populations within the fully developed lymph node. Most recently, lymphotoxin has been implicated in regulation of the microbiota and metabolic disease. Early studies revealed that lymphotoxin might influence composition of the commensal microbiota through its regulation of immunological compartmentalization in the gut. Additionally, several epidemiological studies have linked polymorphisms in lymphotoxin to metabolic disease. Studies exploring the role of lymphotoxin in metabolic disease have demonstrated that lymphotoxin may influence metabolism both directly in the liver and indirectly through regulation of gut immune responses. It now appears that lymphotoxin may bridge the gap between altered composition of the commensal microbiota and metabolism.

Quantitatively different, yet qualitatively alike: a meta-analysis of the mouse core gut microbiome with a view towards the human gut microbiome

Background

A number of human diseases such as obesity and diabetes are associated with changes or imbalances in the gut microbiota (GM). Laboratory mice are commonly used as experimental models for such disorders. The introduction and dynamic development of next generation sequencing techniques have enabled detailed mapping of the GM of both humans and animal models. Nevertheless there is still a significant knowledge gap regarding the human and mouse common GM core and thus the applicability of the latter as an animal model. The aim of the present study was to identify inter- and intra-individual differences and similarities between the GM composition of particular mouse strains and humans.

Methodology/Principal Findings

A total of 1509428 high quality tag-encoded partial 16S rRNA gene sequences determined using 454/FLX Titanium (Roche) pyro-sequencing reflecting the GM composition of 32 human samples from 16 individuals and 88 mouse samples from three laboratory mouse strains commonly used in diabetes research were analyzed using Principal Coordinate Analysis (PCoA), nonparametric multivariate analysis of similarity (ANOSIM) and alpha diversity measures. A reliable cutoff threshold for low abundant taxa estimated on the basis of the present study is recommended for similar trials.

Conclusions/Significance

Distinctive quantitative differences in the relative abundance of most taxonomic groups between the examined categories were found. All investigated mouse strains clustered separately, but with a range of shared features when compared to the human GM. However, both mouse fecal, caecal and human fecal samples shared to a large extent not only representatives of the same phyla, but also a substantial fraction of common genera, where the number of shared genera increased with sequencing depth. In conclusion, the GM of mice and humans is quantitatively different (in terms of abundance of specific phyla and species) but share a large qualitatively similar core.

Holding a grudge: persisting anti-phage CRISPR immunity in multiple human gut microbiomes

The CRISPR (clustered regularly interspaced short palindromic repeats)/Cas (CRISPR-associated) system of bacteria and archaea constitutes a mechanism of acquired adaptive immunity against phages, which is based on genome-encoded markers of previously infecting phage sequences ("spacers"). As a repository of phage sequences, these spacers make the system particularly suitable for elucidating phage-bacteria interactions in metagenomic studies. Recent metagenomic analyses of CRISPRs associated with the human microbiome intriguingly revealed conserved "memory spacers" shared by bacteria in multiple unrelated, geographically separated individuals. Here, we discuss possible avenues for explaining this phenomenon by integrating insights from CRISPR biology and phage-bacteria ecology, with a special focus on the human gut. We further explore the growing body of evidence for the role of CRISPR/Cas in regulating the interplay between bacteria and lysogenic phages, which may be intimately related to the presence of memory spacers and sheds new light on the multifaceted biological and ecological modes of action of CRISPR/Cas.

Beyond phylotyping: understanding the impact of gut microbiota on host biology

BACKGROUND

Microbial constituents of the gut microbiome interact with each other and the host to alter the luminal environment and impact development, motility, and homeostasis of the gut. Powerful methods are becoming available to investigate connections between the gut microbiome and human health. While high-throughput sequencing of 16S rRNA genes can be used to identify and enumerate microbes in the gut, advances in several techniques (e.g., metagenomics, metatranscriptomics, metabolomics, and metaproteomics) are providing a clearer view as to the specific activities of the microbiota in the context of functional host-microbe interactions. Testing emergent hypotheses regarding microbial effects on host biology, which arise from analyses of 'Big Data' generated from massive parallel high-throughput sequencing technology and spectroscopic techniques, to guide translational research is an important goal for the future. Insights regarding the fundamental operating principles of the gut microbiota should lay the foundation for rational manipulation of the microbiota to promote human health.

PURPOSE

In this review, we provide an overview of current research on the gut microbiome emphasizing current state-of-the-art technologies, approaches, and directions for improvement of our understanding of the impact of the gut microbiota with specific focus on gastrointestinal motility disorders.

A pig model of the human gastrointestinal tract

Easy access to next generation sequencing has enabled the rapid analysis of complex microbial populations. To take full advantage of these technologies, animal models enabling the manipulation of human microbiomes and the study of the impact of such perturbations on the host are needed. To this aim we are developing experimentally tractable and clinically relevant pig models of the human adult and infant gastro-intestinal tract. The intestine of germ-free piglets was populated with human adult or infant fecal microbial populations, and the piglets were maintained on solid or milk diet, respectively. Amplicons of 16S rRNA V6 region were deep-sequenced to monitor to what extent the transplanted human microbiomes changed in the pig. Within 24 h of transfer of human fecal microbiome to pigs, bacterial microbiomes rich in Proteobacteria emerged. These populations evolved toward a more diverse composition rich in Bacteroidetes and Firmicutes. In the experiment where infant microbiome was used, the phylogenetic composition of the transplanted bacterial population converged toward that of the human inoculum. A majority of sequences belonged to a relatively small number of operational taxonomic units, whereas at the other end of the abundance spectrum, a large number of rare and transient OTUs were detected. Analysis of fecal and colonic microbiomes originating from the same animal indicate that feces closely replicate the colonic microbiome. We conclude that the pig intestine can be colonized with human fecal microbiomes to generate a realistic model of the human GI tract.

Molecular characterization of the fecal microbiota in patients with nonalcoholic steatohepatitis--a longitudinal study

Background

The human gut microbiota has profound influence on host metabolism and immunity. This study characterized the fecal microbiota in patients with nonalcoholic steatohepatitis (NASH). The relationship between microbiota changes and changes in hepatic steatosis was also studied.

Methods

Fecal microbiota of histology-proven NASH patients and healthy controls was analyzed by 16S ribosomal RNA pyrosequencing. NASH patients were from a previously reported randomized trial on probiotic treatment. Proton-magnetic resonance spectroscopy was performed to monitor changes in intrahepatic triglyceride content (IHTG).

Results

A total of 420,344 16S sequences with acceptable quality were obtained from 16 NASH patients and 22 controls. NASH patients had lower fecal abundance of Faecalibacterium and Anaerosporobacter but higher abundance of Parabacteroides and Allisonella. Partial least-square discriminant analysis yielded a model of 10 genera that discriminated NASH patients from controls. At month 6, 6 of 7 patients in the probiotic group and 4 of 9 patients in the usual care group had improvement in IHTG (P = 0.15). Improvement in IHTG was associated with a reduction in the abundance of Firmicutes (R² = 0.4820, P = 0.0028) and increase in Bacteroidetes (R² = 0.4366, P = 0.0053). This was accompanied by corresponding changes at the class, order and genus levels. In contrast, bacterial biodiversity did not differ between NASH patients and controls, and did not change with probiotic treatment.

Conclusions

NASH patients have fecal dysbiosis, and changes in microbiota correlate with improvement in hepatic steatosis. Further studies are required to investigate the mechanism underlying the interaction between gut microbes and the liver.

Genome-scale modeling of human metabolism - a systems biology approach

Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models - one of the fundamental aspects of systems biology - have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed.

Gut microbiota and obesity: lessons from the microbiome

The distal gut harbours microbial communities that outnumber our own eukaryotic cells. The contribution of the gut microbiota to the development of several diseases (e.g. obesity, type 2 diabetes, steatosis, cardiovascular diseases and inflammatory bowel diseases) is becoming clear, although the causality remains to be proven in humans. Global changes in the gut microbiota have been observed by a number of culture-dependent and culture-independent methods, and while the latter have mostly included 16S ribosomal RNA gene analyses, more recent studies have utilized DNA sequencing of whole-microbial communities. Altogether, these high-throughput methods have facilitated the identification of novel candidate bacteria and, most importantly, metabolic functions that might be associated with obesity and type 2 diabetes. This review discusses the association between specific taxa and obesity, together with the techniques that are used to characterize the gut microbiota in the context of obesity and type 2 diabetes. Recent results are discussed in the framework of the interactions between gut microbiota and host metabolism.

Quantifying the metabolic activities of human-associated microbial communities across multiple ecological scales

Humans are home to complex microbial communities, whose aggregate genomes and their encoded metabolic activities are referred to as the human microbiome. Recently, researchers have begun to appreciate that different human body habitats and the activities of their resident microorganisms can be better understood in ecological terms, as a range of spatial scales encompassing single cells, guilds of microorganisms responsive to a similar substrate, microbial communities, body habitats, and host populations. However, the bulk of the work to date has focused on studies of culturable microorganisms in isolation or on DNA sequencing-based surveys of microbial diversity in small-to-moderate-sized cohorts of individuals. Here, we discuss recent work that highlights the potential for assessing the human microbiome at a range of spatial scales, and for developing novel techniques that bridge multiple levels: for example, through the combination of single-cell methods and metagenomic sequencing. These studies promise to not only provide a much-needed epidemiological and ecological context for mechanistic studies of culturable and genetically tractable microorganisms, but may also lead to the discovery of fundamental rules that govern the assembly and function of host-associated microbial communities.

Species identification and profiling of complex microbial communities using shotgun Illumina sequencing of 16S rRNA amplicon sequences

The high throughput and cost-effectiveness afforded by short-read sequencing technologies, in principle, enable researchers to perform 16S rRNA profiling of complex microbial communities at unprecedented depth and resolution. Existing Illumina sequencing protocols are, however, limited by the fraction of the 16S rRNA gene that is interrogated and therefore limit the resolution and quality of the profiling. To address this, we present the design of a novel protocol for shotgun Illumina sequencing of the bacterial 16S rRNA gene, optimized to amplify more than 90% of sequences in the Greengenes database and with the ability to distinguish nearly twice as many species-level OTUs compared to existing protocols. Using several in silico and experimental datasets, we demonstrate that despite the presence of multiple variable and conserved regions, the resulting shotgun sequences can be used to accurately quantify the constituents of complex microbial communities. The reconstruction of a significant fraction of the 16S rRNA gene also enabled high precision (>90%) in species-level identification thereby opening up potential application of this approach for clinical microbial characterization.

From gut changes to type 2 diabetes remission after gastric bypass surgeries

Increasing evidence suggests that the gut may influence the host's metabolism and ultimately change the outcomes of type 2 diabetes mellitus (T2DM). We review the evidence on the relationship between the gut and T2DM remission after gastric bypass surgery, and discuss the potential mechanisms underlying the above relationship: gut anatomical rearrangement, microbial composition changes, altered gut cells, and gut hormone modulation. However, the exact changes and their relative importance in the metabolic improvements after gastric bypass surgery remain to be further clarified. Elucidating the precise metabolic mechanisms of T2DM resolution after bypass surgery will help to reveal the molecular mechanisms of pathogenesis, and facilitate the development of novel diagnoses and preventative interventions for this common disease.

Geographical variability and environmental risk factors in inflammatory bowel disease

The changing epidemiology of inflammatory bowel disease (IBD) across time and geography suggests that environmental factors play a major role in modifying disease expression. Disease emergence in developing nations suggests that epidemiological evolution is related to westernisation of lifestyle and industrialisation. The strongest environmental associations identified are cigarette smoking and appendectomy, although neither alone explains the variation in incidence of IBD worldwide. Urbanisation of societies, associated with changes in diet, antibiotic use, hygiene status, microbial exposures and pollution have been implicated as potential environmental risk factors for IBD. Changes in socioeconomic status might occur differently in different geographical areas and populations and, consequently, it is important to consider the heterogeneity of risk factors applicable to the individual patient. Environmental risk factors of individual, familial, community-based, country-based and regionally based origin may all contribute to the pathogenesis of IBD. The geographical variation of IBD provides clues for researchers to investigate possible environmental aetiological factors. The present review aims to provide an update of the literature exploring geographical variability in IBD and to explore the environmental risk factors that may account for this variability.

Upper gastrointestinal microbiota and digestive diseases

Metagenomics which combines the power of genomics, bioinformatics, and systems biology, provide new access to the microbial world. Metagenomics permit the genetic analysis of complex microbial populations without requiring prior cultivation. Through the conceptual innovations in metagenomics and the improvements in DNA high-throughput sequencing and bioinformatics analysis technology, gastrointestinal microbiology has entered the metagenomics era and become a hot topic worldwide. Human microbiome research is underway, however, most studies in this area have focused on the composition and function of the intestinal microbiota and the relationship between intestinal microbiota and metabolic diseases (obesity, diabetes, metabolic syndrome, etc.) and intestinal disorders [inflammatory bowel disease, colorectal cancer, irritable bowel syndrome (IBS), etc.]. Few investigations on microbiota have been conducted within the upper gastrointestinal tract (esophagus, stomach and duodenum). The upper gastrointestinal microbiota is essential for several gastrointestinal illnesses, including esophagitis, Barrett’s esophagus, and esophageal carcinoma, gastritis and gastric cancer, small intestinal bacterial overgrowth, IBS and celiac disease. However, the constitution and diversity of the microbiota in different sections of the upper gastrointestinal tract under health and various disease states, as well as the function of microbiota in the pathogenesis of various digestive diseases are still undefined. The current article provides an overview of the recent findings regarding the relationship between upper gastrointestinal microbiota and gastrointestinal diseases; and discusses the study limitations and future directions of upper gastrointestinal microbiota research.