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Recent studies suggest that gut microbiomes of urban-industrialized societies are different from those of traditional peoples. Here we examine the relationship between lifeways and gut microbiota through taxonomic and functional potential characterization of faecal samples from hunter-gatherer and traditional agriculturalist communities in Peru and an urban-industrialized community from the US. We find that in addition to taxonomic and metabolic differences between urban and traditional lifestyles, hunter-gatherers form a distinct sub-group among traditional peoples. As observed in previous studies, we find that Treponema are characteristic of traditional gut microbiomes. Moreover, through genome reconstruction (2.2-2.5 MB, coverage depth × 26-513) and functional potential characterization, we discover these Treponema are diverse, fall outside of pathogenic clades and are similar to Treponema succinifaciens, a known carbohydrate metabolizer in swine. Gut Treponema are found in non-human primates and all traditional peoples studied to date, suggesting they are symbionts lost in urban-industrialized societies.

To study how microbes establish themselves in a mammalian gut environment, we colonized germ-free mice with microbial communities from human, zebrafish, and termite guts, human skin and tongue, soil, and estuarine microbial mats. Bacteria from these foreign environments colonized and persisted in the mouse gut; their capacity to metabolize dietary and host carbohydrates and bile acids correlated with colonization success. Cohousing mice harboring these xenomicrobiota or a mouse cecal microbiota, along with germ-free "bystanders," revealed the success of particular bacterial taxa in invading guts with established communities and empty gut habitats. Unanticipated patterns of ecological succession were observed; for example, a soil-derived bacterium dominated even in the presence of bacteria from other gut communities (zebrafish and termite), and human-derived bacteria colonized germ-free bystander mice before mouse-derived organisms. This approach can be generalized to address a variety of mechanistic questions about succession, including succession in the context of microbiota-directed therapeutics., (Copyright © 2014 Elsevier Inc. All rights reserved.)

The bacteria that colonize humans and our built environments have the potential to influence our health. Microbial communities associated with seven families and their homes over 6 weeks were assessed, including three families that moved their home. Microbial communities differed substantially among homes, and the home microbiome was largely sourced from humans. The microbiota in each home were identifiable by family. Network analysis identified humans as the primary bacterial vector, and a Bayesian method significantly matched individuals to their dwellings. Draft genomes of potential human pathogens observed on a kitchen counter could be matched to the hands of occupants. After a house move, the microbial community in the new house rapidly converged on the microbial community of the occupants' former house, suggesting rapid colonization by the family's microbiota., (Copyright © 2014, American Association for the Advancement of Science.)

We present a performance-optimized algorithm, subsampled open-reference OTU picking, for assigning marker gene (e.g., 16S rRNA) sequences generated on next-generation sequencing platforms to operational taxonomic units (OTUs) for microbial community analysis. This algorithm provides benefits over de novo OTU picking (clustering can be performed largely in parallel, reducing runtime) and closed-reference OTU picking (all reads are clustered, not only those that match a reference database sequence with high similarity). Because more of our algorithm can be run in parallel relative to "classic" open-reference OTU picking, it makes open-reference OTU picking tractable on massive amplicon sequence data sets (though on smaller data sets, "classic" open-reference OTU clustering is often faster). We illustrate that here by applying it to the first 15,000 samples sequenced for the Earth Microbiome Project (1.3 billion V4 16S rRNA amplicons). To the best of our knowledge, this is the largest OTU picking run ever performed, and we estimate that our new algorithm runs in less than 1/5 the time than would be required of "classic" open reference OTU picking. We show that subsampled open-reference OTU picking yields results that are highly correlated with those generated by "classic" open-reference OTU picking through comparisons on three well-studied datasets. An implementation of this algorithm is provided in the popular QIIME software package, which uses uclust for read clustering. All analyses were performed using QIIME's uclust wrappers, though we provide details (aided by the open-source code in our GitHub repository) that will allow implementation of subsampled open-reference OTU picking independently of QIIME (e.g., in a compiled programming language, where runtimes should be further reduced). Our analyses should generalize to other implementations of these OTU picking algorithms. Finally, we present a comparison of parameter settings in QIIME's OTU picking workflows and make recommendations on settings for these free parameters to optimize runtime without reducing the quality of the results. These optimized parameters can vastly decrease the runtime of uclust-based OTU picking in QIIME.

Unlabelled: Glycans form the primary nutritional source for microbes in the human gut, and understanding their metabolism is a critical yet understudied aspect of microbiome research. Here, we present a novel computational pipeline for modeling glycan degradation (GlyDeR) which predicts the glycan degradation potency of 10,000 reference glycans based on either genomic or metagenomic data. We first validated GlyDeR by comparing degradation profiles for genomes in the Human Microbiome Project against KEGG reaction annotations. Next, we applied GlyDeR to the analysis of human and mammalian gut microbial communities, which revealed that the glycan degradation potential of a community is strongly linked to host diet and can be used to predict diet with higher accuracy than sequence data alone. Finally, we show that a microbe's glycan degradation potential is significantly correlated (R = 0.46) with its abundance, with even higher correlations for potential pathogens such as the class Clostridia (R = 0.76). GlyDeR therefore represents an important tool for advancing our understanding of bacterial metabolism in the gut and for the future development of more effective prebiotics for microbial community manipulation., Importance: The increased availability of high-throughput sequencing data has positioned the gut microbiota as a major new focal point for biomedical research. However, despite the expenditure of huge efforts and resources, sequencing-based analysis of the microbiome has uncovered mostly associative relationships between human health and diet, rather than a causal, mechanistic one. In order to utilize the full potential of systems biology approaches, one must first characterize the metabolic requirements of gut bacteria, specifically, the degradation of glycans, which are their primary nutritional source. We developed a computational framework called GlyDeR for integrating expert knowledge along with high-throughput data to uncover important new relationships within glycan metabolism. GlyDeR analyzes particular bacterial (meta)genomes and predicts the potency by which they degrade a variety of different glycans. Based on GlyDeR, we found a clear connection between microbial glycan degradation and human diet, and we suggest a method for the rational design of novel prebiotics., (Copyright © 2014 Eilam, et al.)

Recent advances that allow us to collect more data on DNA sequences and metabolites have increased our understanding of connections between the intestinal microbiota and metabolites at a whole-systems level. We can also now better study the effects of specific microbes on specific metabolites. Here, we review how the microbiota determines levels of specific metabolites, how the metabolite profile develops in infants, and prospects for assessing a person's physiological state based on their microbes and/or metabolites. Although data acquisition technologies have improved, the computational challenges in integrating data from multiple levels remain formidable; developments in this area will significantly improve our ability to interpret current and future data sets., (Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.)

A new study explores the ancient oral microbiome from the well-preserved dental calculus samples of four human individuals who lived during medieval times, using a suite of genomic, proteomic and microscopic approaches. The authors investigate the evolution of dental pathogens by reconstructing the genome of the periodontal pathogen Tannerella forsythia and also identify antibiotic resistance genes, bacterial virulence factors and host immune defense proteins.

Vaginally administered antiviral agents may reduce the risk of HIV and HSV acquisition. Delivery of these drugs using intravaginal rings (IVRs) holds the potential benefits of improving adherence and decreasing systemic exposure, while maintaining steady-state drug levels in the vaginal tract. Elucidating how IVRs interact with the vaginal microbiome constitutes a critical step in evaluating the safety of these devices, as shifts the vaginal microbiome have been linked with several disease states. To date, clinical IVR trials have relied on culture-dependent methods that omit the high diversity of unculturable microbial population. Longitudinal, culture-independent characterization of the microbiota in vaginal samples from 6 women with recurrent genital HSV who used an acyclovir IVR was carried out and compared to the communities developing in biofilms on the IVR surface. The analysis utilized Illumina MiSeq sequence datasets generated from bar-coded amplicons of 16S rRNA gene fragments. Specific taxa in the vaginal communities of the study participants were found to be associated with the duration of recurrent genital HSV status and the number of HSV outbreaks. Taxonomic comparison of the vaginal and IVR biofilm communities did not reveal any significant differences, suggesting that the IVRs were not systematically enriched with members of the vaginal microbiome. Device usage did not alter the participants' vaginal microbial communities, within the confines of the current study design. Rigorous, molecular analysis of the effects of intravaginal devices on the corresponding microbial communities shows promise for integration with traditional approaches in the clinical evaluation of candidate products., (Copyright © 2013 Elsevier B.V. All rights reserved.)

We investigate how host mucus glycan composition interacts with dietary carbohydrate content to influence the composition and expressed functions of a human gut community. The humanized gnotobiotic mice mimic humans with a nonsecretor phenotype due to knockout of their α1-2 fucosyltransferase (Fut2) gene. The fecal microbiota of Fut2(-) mice that lack fucosylated host glycans show decreased alpha diversity relative to Fut2(+) mice and exhibit significant differences in community composition. A glucose-rich plant polysaccharide-deficient (PD) diet exerted a strong effect on the microbiota membership but eliminated the effect of Fut2 genotype. Additionally fecal metabolites predicted host genotype in mice on a polysaccharide-rich standard diet but not on a PD diet. A more detailed mechanistic analysis of these interactions involved colonization of gnotobiotic Fut2(+) and Fut2(-) mice with Bacteroides thetaiotaomicron, a prominent member of the human gut microbiota known to adaptively forage host mucosal glycans when dietary polysaccharides are absent. Within Fut2(-) mice, the B. thetaiotaomicron fucose catabolic pathway was markedly down-regulated, whereas BT4241-4247, an operon responsive to terminal β-galactose, the precursor that accumulates in the Fut2(-) mice, was significantly up-regulated. These changes in B. thetaiotaomicron gene expression were only evident in mice fed a PD diet, wherein B. thetaiotaomicron relies on host mucus consumption. Furthermore, up-regulation of the BT4241-4247 operon was also seen in humanized Fut2(-) mice. Together, these data demonstrate that differences in host genotype that affect the carbohydrate landscape of the distal gut interact with diet to alter the composition and function of resident microbes in a diet-dependent manner.

The role of specific gut microbes in shaping body composition remains unclear. We transplanted fecal microbiota from adult female twin pairs discordant for obesity into germ-free mice fed low-fat mouse chow, as well as diets representing different levels of saturated fat and fruit and vegetable consumption typical of the U.S. diet. Increased total body and fat mass, as well as obesity-associated metabolic phenotypes, were transmissible with uncultured fecal communities and with their corresponding fecal bacterial culture collections. Cohousing mice harboring an obese twin's microbiota (Ob) with mice containing the lean co-twin's microbiota (Ln) prevented the development of increased body mass and obesity-associated metabolic phenotypes in Ob cage mates. Rescue correlated with invasion of specific members of Bacteroidetes from the Ln microbiota into Ob microbiota and was diet-dependent. These findings reveal transmissible, rapid, and modifiable effects of diet-by-microbiota interactions.

Large-scale characterization of the human microbiota has largely focused on Western adults, yet these populations may be uncharacteristic because of their diets and lifestyles. In particular, the rise of "Western diseases" may in part stem from reduced exposure to, or even loss of, microbes with which humans have coevolved. Here, we review beneficial microbes associated with pathogen resistance, highlighting the emerging role of complex microbial communities in protecting against disease. We discuss ways in which modern lifestyles and practices may deplete physiologically important microbiota, and explore prospects for reintroducing or encouraging the growth of beneficial microbes to promote the restoration of healthy microbial ecosystems., (Copyright © 2013 WILEY Periodicals, Inc.)

Background & Aims: Diet has major effects on the intestinal microbiota, but the exact mechanisms that alter complex microbial communities have been difficult to elucidate. In addition to the direct influence that diet exerts on microbes, changes in microbiota composition and function can alter host functions such as gastrointestinal (GI) transit time, which in turn can further affect the microbiota., Methods: We investigated the relationships among diet, GI motility, and the intestinal microbiota using mice that are germ-free (GF) or humanized (ex-GF mice colonized with human fecal microbiota)., Results: Analysis of gut motility revealed that humanized mice fed a standard polysaccharide-rich diet had faster GI transit and increased colonic contractility compared with GF mice. Humanized mice with faster transit due to administration of polyethylene glycol or a nonfermentable cellulose-based diet had similar changes in gut microbiota composition, indicating that diet can modify GI transit, which then affects the composition of the microbial community. However, altered transit in mice fed a diet of fermentable fructooligosaccharide indicates that diet can change gut microbial function, which can affect GI transit., Conclusions: Based on studies in humanized mice, diet can affect GI transit through microbiota-dependent or microbiota-independent pathways, depending on the type of dietary change. The effect of the microbiota on transit largely depends on the amount and type (fermentable vs nonfermentable) of polysaccharides present in the diet. These results have implications for disorders that affect GI transit and gut microbial communities, including irritable bowel syndrome and inflammatory bowel disease., (Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.)

The human gut microbiome plays an important role in the metabolism of xenobiotics. In a recent issue of Cell, Maurice et al. (2013) identify the active members of the gut microbiome and show how gene-expression profiles change within the gut microbial community in response to antibiotics and host-targeted xenobiotics., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Kwashiorkor, an enigmatic form of severe acute malnutrition, is the consequence of inadequate nutrient intake plus additional environmental insults. To investigate the role of the gut microbiome, we studied 317 Malawian twin pairs during the first 3 years of life. During this time, half of the twin pairs remained well nourished, whereas 43% became discordant, and 7% manifested concordance for acute malnutrition. Both children in twin pairs discordant for kwashiorkor were treated with a peanut-based, ready-to-use therapeutic food (RUTF). Time-series metagenomic studies revealed that RUTF produced a transient maturation of metabolic functions in kwashiorkor gut microbiomes that regressed when administration of RUTF was stopped. Previously frozen fecal communities from several discordant pairs were each transplanted into gnotobiotic mice. The combination of Malawian diet and kwashiorkor microbiome produced marked weight loss in recipient mice, accompanied by perturbations in amino acid, carbohydrate, and intermediary metabolism that were only transiently ameliorated with RUTF. These findings implicate the gut microbiome as a causal factor in kwashiorkor.

Obesity is a highly heritable disease driven by complex interactions between genetic and environmental factors. Human genome-wide association studies (GWAS) have identified a number of loci contributing to obesity; however, a major limitation of these studies is the inability to assess environmental interactions common to obesity. Using a systems genetics approach, we measured obesity traits, global gene expression, and gut microbiota composition in response to a high-fat/high-sucrose (HF/HS) diet of more than 100 inbred strains of mice. Here we show that HF/HS feeding promotes robust, strain-specific changes in obesity that are not accounted for by food intake and provide evidence for a genetically determined set point for obesity. GWAS analysis identified 11 genome-wide significant loci associated with obesity traits, several of which overlap with loci identified in human studies. We also show strong relationships between genotype and gut microbiota plasticity during HF/HS feeding and identify gut microbial phylotypes associated with obesity., (Copyright © 2013 Elsevier Inc. All rights reserved.)

High-throughput DNA sequencing technologies, coupled with advanced bioinformatics tools, have enabled rapid advances in microbial ecology and our understanding of the human microbiome. QIIME (Quantitative Insights Into Microbial Ecology) is an open-source bioinformatics software package designed for microbial community analysis based on DNA sequence data, which provides a single analysis framework for analysis of raw sequence data through publication-quality statistical analyses and interactive visualizations. In this chapter, we demonstrate the use of the QIIME pipeline to analyze microbial communities obtained from several sites on the bodies of transgenic and wild-type mice, as assessed using 16S rRNA gene sequences generated on the Illumina MiSeq platform. We present our recommended pipeline for performing microbial community analysis and provide guidelines for making critical choices in the process. We present examples of some of the types of analyses that are enabled by QIIME and discuss how other tools, such as phyloseq and R, can be applied to expand upon these analyses., (© 2013 Elsevier Inc. All rights reserved.)

Rapidly developing sequencing methods and analytical techniques are enhancing our ability to understand the human microbiome, and, indeed, how the microbiome and its constituents are defined. This review highlights recent research that expands our ability to understand the human microbiome on different spatial and temporal scales, including daily time series datasets spanning months. Furthermore, emerging concepts related to defining operational taxonomic units, diversity indices, core versus transient microbiomes, and the possibility of enterotypes are discussed. Additional advances in sequencing technology and in our understanding of the microbiome will provide exciting prospects for exploiting the microbiota for personalized medicine., (© 2012 International Life Sciences Institute.)

The human body harbors 10 to 100 trillion microbes, mainly bacteria in our gut, which greatly outnumber our own human cells. This bacterial assemblage, referred to as the human microbiota, plays a fundamental role in our well-being. Deviations from healthy microbial compositions (dysbiosis) have been linked with important human diseases, including inflammation-linked disorders, such as allergies, obesity, and inflammatory bowel disease. Characterizing the temporal variations and community membership of the healthy human microbiome is critical to accurately identify the significant deviations from normality that could be associated with disease states. However, the diversity of the human microbiome varies between body sites, between patients, and over time. Environmental differences have also been shown to play a role in shaping the human microbiome in different cultures, requiring that the healthy human microbiome be characterized across life spans, ethnicities, nationalities, cultures, and geographic locales. In this article we summarize our knowledge on the microbial composition of the 5 best-characterized body sites (gut, skin, oral, airways, and vagina), focusing on interpersonal and intrapersonal variations and our current understanding of the sources of this variation., (Copyright © 2012 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.)

The human gut harbors diverse microbes that play a fundamental role in the well-being of their host. The constituents of the microbiota--bacteria, viruses, and eukaryotes--have been shown to interact with one another and with the host immune system in ways that influence the development of disease. We review these interactions and suggest that a holistic approach to studying the microbiota that goes beyond characterization of community composition and encompasses dynamic interactions between all components of the microbiota and host tissue over time will be crucial for building predictive models for diagnosis and treatment of diseases linked to imbalances in our microbiota., (Copyright © 2012 Elsevier Inc. All rights reserved.)