A core gut microbiome in obese and lean twins.

The human distal gut harbours a vast ensemble of microbes (the microbiota) that provide important metabolic capabilities, including the ability to extract energy from otherwise indigestible dietary polysaccharides. Studies of a few unrelated, healthy adults have revealed substantial diversity in their gut communities, as measured by sequencing 16S rRNA genes, yet how this diversity relates to function and to the rest of the genes in the collective genomes of the microbiota (the gut microbiome) remains obscure. Studies of lean and obese mice suggest that the gut microbiota affects energy balance by influencing the efficiency of calorie harvest from the diet, and how this harvested energy is used and stored. Here we characterize the faecal microbial communities of adult female monozygotic and dizygotic twin pairs concordant for leanness or obesity, and their mothers, to address how host genotype, environmental exposure and host adiposity influence the gut microbiome. Analysis of 154 individuals yielded 9,920 near full-length and 1,937,461 partial bacterial 16S rRNA sequences, plus 2.14 gigabases from their microbiomes. The results reveal that the human gut microbiome is shared among family members, but that each person's gut microbial community varies in the specific bacterial lineages present, with a comparable degree of co-variation between adult monozygotic and dizygotic twin pairs. However, there was a wide array of shared microbial genes among sampled individuals, comprising an extensive, identifiable 'core microbiome' at the gene, rather than at the organismal lineage, level. Obesity is associated with phylum-level changes in the microbiota, reduced bacterial diversity and altered representation of bacterial genes and metabolic pathways. These results demonstrate that a diversity of organismal assemblages can nonetheless yield a core microbiome at a functional level, and that deviations from this core are associated with different physiological states (obese compared with lean).

The human microbiome project.

A strategy to understand the microbial components of the human genetic and metabolic landscape and how they contribute to normal physiology and predisposition to disease.

Regulation of myocardial ketone body metabolism by the gut microbiota during nutrient deprivation.

Studies in mice indicate that the gut microbiota promotes energy harvest and storage from components of the diet when these components are plentiful. Here we examine how the microbiota shapes host metabolic and physiologic adaptations to periods of nutrient deprivation. Germ-free (GF) mice and mice who had received a gut microbiota transplant from conventionally raised donors were compared in the fed and fasted states by using functional genomic, biochemical, and physiologic assays. A 24-h fast produces a marked change in gut microbial ecology. Short-chain fatty acids generated from microbial fermentation of available glycans are maintained at higher levels compared with GF controls. During fasting, a microbiota-dependent, Ppar alpha-regulated increase in hepatic ketogenesis occurs, and myocardial metabolism is directed to ketone body utilization. Analyses of heart rate, hydraulic work, and output, mitochondrial morphology, number, and respiration, plus ketone body, fatty acid, and glucose oxidation in isolated perfused working hearts from GF and colonized animals (combined with in vivo assessments of myocardial physiology) revealed that the fasted GF heart is able to sustain its performance by increasing glucose utilization, but heart weight, measured echocardiographically or as wet mass and normalized to tibial length or lean body weight, is significantly reduced in both fasted and fed mice. This myocardial-mass phenotype is completely reversed in GF mice by consumption of a ketogenic diet. Together, these results illustrate benefits provided by the gut microbiota during periods of nutrient deprivation, and emphasize the importance of further exploring the relationship between gut microbes and cardiovascular health.

Global patterns in the biogeography of bacterial taxa.

Bacteria control major nutrient cycles and directly influence plant, animal and human health. However, we know relatively little about the forces shaping their large-scale ecological ranges. Here, we reveal patterns in the distribution of individual bacterial taxa at multiple levels of phylogenetic resolution within and between Earth's major habitat types. Our analyses suggest that while macro-scale habitats structure bacterial distribution to some degree, abundant bacteria (i.e. detectable using 16S rRNA gene sequencing methods) are confined to single assemblages. Additionally, we show that the most cosmopolitan taxa are also the most abundant in individual assemblages. These results add to the growing body of data that support that the diversity of the overall bacterial metagenome is tremendous. The mechanisms governing microbial distribution remain poorly understood, but our analyses provide a framework with which to test the importance of macro-ecological environmental gradients, relative abundance, neutral processes and the ecological strategies of individual taxa in structuring microbial communities.

Error-correcting barcoded primers for pyrosequencing hundreds of samples in multiplex.

We constructed error-correcting DNA barcodes that allow one run of a massively parallel pyrosequencer to process up to 1,544 samples simultaneously. Using these barcodes we processed bacterial 16S rRNA gene sequences representing microbial communities in 286 environmental samples, corrected 92% of sample assignment errors, and thus characterized nearly as many 16S rRNA genes as have been sequenced to date by Sanger sequencing.

The influence of sex, handedness, and washing on the diversity of hand surface bacteria.

Bacteria thrive on and within the human body. One of the largest human-associated microbial habitats is the skin surface, which harbors large numbers of bacteria that can have important effects on health. We examined the palmar surfaces of the dominant and nondominant hands of 51 healthy young adult volunteers to characterize bacterial diversity on hands and to assess its variability within and between individuals. We used a novel pyrosequencing-based method that allowed us to survey hand surface bacterial communities at an unprecedented level of detail. The diversity of skin-associated bacterial communities was surprisingly high; a typical hand surface harbored >150 unique species-level bacterial phylotypes, and we identified a total of 4,742 unique phylotypes across all of the hands examined. Although there was a core set of bacterial taxa commonly found on the palm surface, we observed pronounced intra- and interpersonal variation in bacterial community composition: hands from the same individual shared only 17% of their phylotypes, with different individuals sharing only 13%. Women had significantly higher diversity than men, and community composition was significantly affected by handedness, time since last hand washing, and an individual's sex. The variation within and between individuals in microbial ecology illustrated by this study emphasizes the challenges inherent in defining what constitutes a "healthy" bacterial community; addressing these challenges will be critical for the International Human Microbiome Project.

The convergence of carbohydrate active gene repertoires in human gut microbes.

The extreme variation in gene content among phylogenetically related microorganisms suggests that gene acquisition, expansion, and loss are important evolutionary forces for adaptation to new environments. Accordingly, phylogenetically disparate organisms that share a habitat may converge in gene content as they adapt to confront shared challenges. This response should be especially pronounced for functional genes that are important for survival in a particular habitat. We illustrate this principle by showing that the repertoires of two different types of carbohydrate-active enzymes, glycoside hydrolases and glycosyltransferases, have converged in bacteria and archaea that live in the human gut and that this convergence is largely due to horizontal gene transfer rather than gene family expansion. We also identify gut microbes that may have more similar dietary niches in the human gut than would be expected based on phylogeny. The techniques used to obtain these results should be broadly applicable to understanding the functional genes and evolutionary processes important for adaptation in many environments and useful for interpreting the large number of reference microbial genome sequences being generated for the International Human Microbiome Project.

High-fat diet determines the composition of the murine gut microbiome independently of obesity.

BACKGROUND & AIMS: The composition of the gut microbiome is affected by host phenotype, genotype, immune function, and diet. Here, we used the phenotype of RELMbeta knockout (KO) mice to assess the influence of these factors. METHODS: Both wild-type and RELMbeta KO mice were lean on a standard chow diet, but, upon switching to a high-fat diet, wild-type mice became obese, whereas RELMbeta KO mice remained comparatively lean. To investigate the influence of diet, genotype, and obesity on microbiome composition, we used deep sequencing to characterize 25,790 16S rDNA sequences from uncultured bacterial communities from both genotypes on both diets. RESULTS: We found large alterations associated with switching to the high-fat diet, including a decrease in Bacteroidetes and an increase in both Firmicutes and Proteobacteria. This was seen for both genotypes (ie, in the presence and absence of obesity), indicating that the high-fat diet itself, and not the obese state, mainly accounted for the observed changes in the gut microbiota. The RELMbeta genotype also modestly influenced microbiome composition independently of diet. Metagenomic analysis of 537,604 sequence reads documented extensive changes in gene content because of a high-fat diet, including an increase in transporters and 2-component sensor responders as well as a general decrease in metabolic genes. Unexpectedly, we found a substantial amount of murine DNA in our samples that increased in proportion on a high-fat diet. CONCLUSIONS: These results demonstrate the importance of diet as a determinant of gut microbiome composition and suggest the need to control for dietary variation when evaluating the composition of the human gut microbiome.

CodonExplorer: an online tool for analyzing codon usage and sequence composition, scaling from genes to genomes.

DNA composition in general, and codon usage in particular, is crucial for understanding gene function and evolution. CodonExplorer, available online at http://bmf.colorado.edu/codonexplorer/, is an online tool and interactive database that contains millions of genes, allowing rapid exploration of the factors governing gene and genome compositional evolution and exploiting GC content and codon usage frequency to identify genes with composition suggesting high levels of expression or horizontal transfer.

The macaque gut microbiome in health, lentiviral infection, and chronic enterocolitis.

The vertebrate gut harbors a vast community of bacterial mutualists, the composition of which is modulated by the host immune system. Many gastrointestinal (GI) diseases are expected to be associated with disruptions of host-bacterial interactions, but relatively few comprehensive studies have been reported. We have used the rhesus macaque model to investigate forces shaping GI bacterial communities. We used DNA bar coding and pyrosequencing to characterize 141,000 sequences of 16S rRNA genes obtained from 100 uncultured GI bacterial samples, allowing quantitative analysis of community composition in health and disease. Microbial communities of macaques were distinct from those of mice and humans in both abundance and types of taxa present. The macaque communities differed among samples from intestinal mucosa, colonic contents, and stool, paralleling studies of humans. Communities also differed among animals, over time within individual animals, and between males and females. To investigate changes associated with disease, samples of colonic contents taken at necropsy were compared between healthy animals and animals with colitis and undergoing antibiotic therapy. Communities from diseased and healthy animals also differed significantly in composition. This work provides comprehensive data and improved methods for studying the role of commensal microbiota in macaque models of GI diseases and provides a model for the large-scale screening of the human gut microbiome.

Evolution of symbiotic bacteria in the distal human intestine.

The adult human intestine contains trillions of bacteria, representing hundreds of species and thousands of subspecies. Little is known about the selective pressures that have shaped and are shaping this community's component species, which are dominated by members of the Bacteroidetes and Firmicutes divisions. To examine how the intestinal environment affects microbial genome evolution, we have sequenced the genomes of two members of the normal distal human gut microbiota, Bacteroides vulgatus and Bacteroides distasonis, and by comparison with the few other sequenced gut and non-gut Bacteroidetes, analyzed their niche and habitat adaptations. The results show that lateral gene transfer, mobile elements, and gene amplification have played important roles in affecting the ability of gut-dwelling Bacteroidetes to vary their cell surface, sense their environment, and harvest nutrient resources present in the distal intestine. Our findings show that these processes have been a driving force in the adaptation of Bacteroidetes to the distal gut environment, and emphasize the importance of considering the evolution of humans from an additional perspective, namely the evolution of our microbiomes.

Host-bacterial coevolution and the search for new drug targets.

Understanding the coevolution between humans and our microbial symbionts and pathogens requires complementary approaches, ranging from community analysis to in-depth analysis of individual genomes. Here we review the evidence for coevolution between symbionts and their hosts, the role of horizontal gene transfer in coevolution, and genomic and metagenomic approaches to identify drug targets. Recent studies have shown that our symbiotic microbes confer many metabolic capabilities that our mammalian genomes lack, and that targeting mechanisms of horizontal gene transfer is a promising new direction for drug discovery. Gnotobiotic ('germ-free') mice are an especially exciting new tool for unraveling the function of microbes, whether individually or in the context of complex communities.

Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale.

Soils harbor enormously diverse bacterial populations, and soil bacterial communities can vary greatly in composition across space. However, our understanding of the specific changes in soil bacterial community structure that occur across larger spatial scales is limited because most previous work has focused on either surveying a relatively small number of soils in detail or analyzing a larger number of soils with techniques that provide little detail about the phylogenetic structure of the bacterial communities. Here we used a bar-coded pyrosequencing technique to characterize bacterial communities in 88 soils from across North and South America, obtaining an average of 1,501 sequences per soil. We found that overall bacterial community composition, as measured by pairwise UniFrac distances, was significantly correlated with differences in soil pH (r = 0.79), largely driven by changes in the relative abundances of Acidobacteria, Actinobacteria, and Bacteroidetes across the range of soil pHs. In addition, soil pH explains a significant portion of the variability associated with observed changes in the phylogenetic structure within each dominant lineage. The overall phylogenetic diversity of the bacterial communities was also correlated with soil pH (R(2) = 0.50), with peak diversity in soils with near-neutral pHs. Together, these results suggest that the structure of soil bacterial communities is predictable, to some degree, across larger spatial scales, and the effect of soil pH on bacterial community composition is evident at even relatively coarse levels of taxonomic resolution.

Characterization of airborne microbial communities at a high-elevation site and their potential to act as atmospheric ice nuclei.

Bacteria and fungi are ubiquitous in the atmosphere. The diversity and abundance of airborne microbes may be strongly influenced by atmospheric conditions or even influence atmospheric conditions themselves by acting as ice nucleators. However, few comprehensive studies have described the diversity and dynamics of airborne bacteria and fungi based on culture-independent techniques. We document atmospheric microbial abundance, community composition, and ice nucleation at a high-elevation site in northwestern Colorado. We used a standard small-subunit rRNA gene Sanger sequencing approach for total microbial community analysis and a bacteria-specific 16S rRNA bar-coded pyrosequencing approach (4,864 sequences total). During the 2-week collection period, total microbial abundances were relatively constant, ranging from 9.6 x 10(5) to 6.6 x 10(6) cells m(-3) of air, and the diversity and composition of the airborne microbial communities were also relatively static. Bacteria and fungi were nearly equivalent, and members of the proteobacterial groups Burkholderiales and Moraxellaceae (particularly the genus Psychrobacter) were dominant. These taxa were not always the most abundant in freshly fallen snow samples collected at this site. Although there was minimal variability in microbial abundances and composition within the atmosphere, the number of biological ice nuclei increased significantly during periods of high relative humidity. However, these changes in ice nuclei numbers were not associated with changes in the relative abundances of the most commonly studied ice-nucleating bacteria.

CodonExplorer: an interactive online database for the analysis of codon usage and sequence composition.

The analysis of DNA composition and codon usage reveals many factors that influence the evolution of genes and genomes. In this chapter, we show how to use CodonExplorer, a web tool and interactive database that contains millions of genes, to better understand the principles governing evolution at the single gene and whole-genome level. We present principles and practical procedures for using analyses of GC content and codon usage frequency to identify highly expressed or horizontally transferred genes and to study the relative contribution of different types of mutation to gene and genome composition. CodonExplorer's combination of a user-friendly web interface and a comprehensive genomic database makes these diverse analyses fast and straightforward to perform. CodonExplorer is thus a powerful tool that facilitates and automates a wide range of compositional analyses.

Short pyrosequencing reads suffice for accurate microbial community analysis.

Pyrosequencing technology allows us to characterize microbial communities using 16S ribosomal RNA (rRNA) sequences orders of magnitude faster and more cheaply than has previously been possible. However, results from different studies using pyrosequencing and traditional sequencing are often difficult to compare, because amplicons covering different regions of the rRNA might yield different conclusions. We used sequences from over 200 globally dispersed environments to test whether studies that used similar primers clustered together mistakenly, without regard to environment. We then tested whether primer choice affects sequence-based community analyses using UniFrac, our recently-developed method for comparing microbial communities. We performed three tests of primer effects. We tested whether different simulated amplicons generated the same UniFrac clustering results as near-full-length sequences for three recent large-scale studies of microbial communities in the mouse and human gut, and the Guerrero Negro microbial mat. We then repeated this analysis for short sequences (100-, 150-, 200- and 250-base reads) resembling those produced by pyrosequencing. The results show that sequencing effort is best focused on gathering more short sequences rather than fewer longer ones, provided that the primers are chosen wisely, and that community comparison methods such as UniFrac are surprisingly robust to variation in the region sequenced.

Bioinformatics assessment of beta-myosin mutations reveals myosin's high sensitivity to mutations.

More than 200 mutations in the beta-myosin gene (MYH7) that cause clinically distinct cardiac and/or skeletal myopathies have been reported, but to date, no comprehensive statistical analysis of these mutations has been performed. As a part of this review, we developed a new interactive database and research tool called MyoMAPR (Myopathic Mutation Analysis Profiler and Repository). We report that the distribution of mutations along the beta-myosin gene is not homogeneous, and that myosin is a highly constrained molecule with an uncommon sensitivity to amino acid substitutions. Increasing knowledge of the characteristics of MH7 mutations may provide a valuable resource for scientists and clinicians studying diagnosis, risk stratification, and treatment of disease associated with these mutations.

UniFrac--an online tool for comparing microbial community diversity in a phylogenetic context.

BACKGROUND: Moving beyond pairwise significance tests to compare many microbial communities simultaneously is critical for understanding large-scale trends in microbial ecology and community assembly. Techniques that allow microbial communities to be compared in a phylogenetic context are rapidly gaining acceptance, but the widespread application of these techniques has been hindered by the difficulty of performing the analyses. RESULTS: We introduce UniFrac, a web application available at http://bmf.colorado.edu/unifrac, that allows several phylogenetic tests for differences among communities to be easily applied and interpreted. We demonstrate the use of UniFrac to cluster multiple environments, and to test which environments are significantly different. We show that analysis of previously published sequences from the Columbia river, its estuary, and the adjacent coastal ocean using the UniFrac interface provided insights that were not apparent from the initial data analysis, which used other commonly employed techniques to compare the communities. CONCLUSION: UniFrac provides easy access to powerful multivariate techniques for comparing microbial communities in a phylogenetic context. We thus expect that it will provide a completely new picture of many microbial interactions and processes in both environmental and medical contexts.

Using the nucleotide substitution rate matrix to detect horizontal gene transfer.

BACKGROUND: Horizontal gene transfer (HGT) has allowed bacteria to evolve many new capabilities. Because transferred genes perform many medically important functions, such as conferring antibiotic resistance, improved detection of horizontally transferred genes from sequence data would be an important advance. Existing sequence-based methods for detecting HGT focus on changes in nucleotide composition or on differences between gene and genome phylogenies; these methods have high error rates. RESULTS: First, we introduce a new class of methods for detecting HGT based on the changes in nucleotide substitution rates that occur when a gene is transferred to a new organism. Our new methods discriminate simulated HGT events with an error rate up to 10 times lower than does GC content. Use of models that are not time-reversible is crucial for detecting HGT. Second, we show that using combinations of multiple predictors of HGT offers substantial improvements over using any single predictor, yielding as much as a factor of 18 improvement in performance (a maximum reduction in error rate from 38% to about 3%). Multiple predictors were combined by using the random forests machine learning algorithm to identify optimal classifiers that separate HGT from non-HGT trees. CONCLUSION: The new class of HGT-detection methods introduced here combines advantages of phylogenetic and compositional HGT-detection techniques. These new techniques offer order-of-magnitude improvements over compositional methods because they are better able to discriminate HGT from non-HGT trees under a wide range of simulated conditions. We also found that combining multiple measures of HGT is essential for detecting a wide range of HGT events. These novel indicators of horizontal transfer will be widely useful in detecting HGT events linked to the evolution of important bacterial traits, such as antibiotic resistance and pathogenicity.

Fast-Find: a novel computational approach to analyzing combinatorial motifs.

BACKGROUND: Many vital biological processes, including transcription and splicing, require a combination of short, degenerate sequence patterns, or motifs, adjacent to defined sequence features. Although these motifs occur frequently by chance, they only have biological meaning within a specific context. Identifying transcripts that contain meaningful combinations of patterns is thus an important problem, which existing tools address poorly. RESULTS: Here we present a new approach, Fast-FIND (Fast-Fully Indexed Nucleotide Database), that uses a relational database to support rapid indexed searches for arbitrary combinations of patterns defined either by sequence or composition. Fast-FIND is easy to implement, takes less than a second to search the entire Drosophila genome sequence for arbitrary patterns adjacent to sites of alternative polyadenylation, and is sufficiently fast to allow sensitivity analysis on the patterns. We have applied this approach to identify transcripts that contain combinations of sequence motifs for RNA-binding proteins that may regulate alternative polyadenylation. CONCLUSION: Fast-FIND provides an efficient way to identify transcripts that are potentially regulated via alternative polyadenylation. We have used it to generate hypotheses about interactions between specific polyadenylation factors, which we will test experimentally.