Luke K. Ursell

Gut microbiota from twins discordant for obesity modulate metabolism in mice.

Introduction Establishing whether specific structural and functional configurations of a human gut microbiota are causally related to a given physiologic or disease phenotype is challenging. Twins discordant for obesity provide an opportunity to examine interrelations between obesity and its associated metabolic disorders, diet, and the gut microbiota. Transplanting the intact uncultured or cultured human fecal microbiota from each member of a discordant twin pair into separate groups of recipient germfree mice permits the donors’ communities to be replicated, differences between their properties to be identified, the impact of these differences on body composition and metabolic phenotypes to be discerned, and the effects of diet-by-microbiota interactions to be analyzed. In addition, cohousing coprophagic mice harboring transplanted microbiota from discordant pairs provides an opportunity to determine which bacterial taxa invade the gut communities of cage mates, how invasion correlates with host phenotypes, and how invasion and microbial niche are affected by human diets. Cohousing Ln and Ob mice prevents increased adiposity in Ob cage mates (Ob). (A) Adiposity change after 10 days of cohousing. *P < 0.05 versus Ob controls (Student’s t test). (B) Bacteroidales from Ln microbiota invade Ob microbiota. Columns show individual mice. Methods Separate groups of germfree mice were colonized with uncultured fecal microbiota from each member of four twin pairs discordant for obesity or with culture collections from an obese (Ob) or lean (Ln) co-twin. Animals were fed a mouse chow low in fat and rich in plant polysaccharides, or one of two diets reflecting the upper or lower tertiles of consumption of saturated fats and fruits and vegetables based on the U.S. National Health and Nutrition Examination Survey (NHANES). Ln or Ob mice were cohoused 5 days after colonization. Body composition changes were defined by quantitative magnetic resonance. Microbiota or microbiome structure, gene expression, and metabolism were assayed by 16S ribosomal RNA profiling, whole-community shotgun sequencing, RNA-sequencing, and mass spectrometry. Host gene expression and metabolism were also characterized. Results and Discussion The intact uncultured and culturable bacterial component of Ob co-twins’ fecal microbiota conveyed significantly greater increases in body mass and adiposity than those of Ln communities. Differences in body composition were correlated with differences in fermentation of short-chain fatty acids (increased in Ln), metabolism of branched-chain amino acids (increased in Ob), and microbial transformation of bile acid species (increased in Ln and correlated with down-regulation of host farnesoid X receptor signaling). Cohousing Ln and Ob mice prevented development of increased adiposity and body mass in Ob cage mates and transformed their microbiota’s metabolic profile to a leanlike state. Transformation correlated with invasion of members of Bacteroidales from Ln into Ob microbiota. Invasion and phenotypic rescue were diet-dependent and occurred with the diet representing the lower tertile of U.S. consumption of saturated fats, and upper tertile of fruits and vegetables, but not with the diet representing the upper tertile of saturated fats, and lower tertile of fruit and vegetable consumption. These results reveal that transmissible and modifiable interactions between diet and microbiota influence host biology. Transforming Fat to Thin How much does the microbiota influence the hosts phenotype? Ridaura et al. (1241214 ; see the Perspective by Walker and Parkhill) obtained uncultured fecal microbiota from twin pairs discordant for body mass and transplanted them into adult germ-free mice. It was discovered that adiposity is transmissible from human to mouse and that it was associated with changes in serum levels of branched-chain amino acids. Moreover, obese-phenotype mice were invaded by members of the Bacteroidales from the lean mice, but, happily, the lean animals resisted invasion by the obese microbiota. Mice carrying gut bacteria from lean humans protect their cage mates from the effects of gut bacteria from fat humans. [Also see Perspective by Walker and Parkhill] 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.

The Impact of the Gut Microbiota on Human Health: An Integrative View

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.

Gut Microbiomes of Malawian Twin Pairs Discordant for Kwashiorkor

Not Just Wasting Malnutrition is well known in Malawi, including a severe form—kwashiorkor—in which children do not simply waste away, they also suffer edema, liver damage, skin ulceration, and anorexia. Smith et al. (p. 548; see the Perspective by Relman) investigated the microbiota of pairs of twins in Malawian villages and found notable differences in the composition of the gut microbiota in children with kwashiorkor. In these children, a bacterial species related to Desulfovibrio, which has been associated with bowel disease and inflammation, was noticeable. When the fecal flora from either the healthy or the sick twin was transplanted into groups of germ-free mice, the mice that received the kwashiorkor sample started to lose weight, like their human counterpart. Genomic analyses of gut microbiota explain responses to dietary therapy for severe malnutrition. [Also see Perspective by Relman] 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.

Genetic Control of Obesity and Gut Microbiota Composition in Response to High-Fat, High-Sucrose Diet in Mice

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.

Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences

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.

Advancing Our Understanding of the Human Microbiome Using QIIME

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.

Complex interactions among diet, gastrointestinal transit, and gut microbiota in humanized mice.

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.

Defining the human microbiome

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.

The interpersonal and intrapersonal diversity of human-associated microbiota in key body sites

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.

Genetically dictated change in host mucus carbohydrate landscape exerts a diet-dependent effect on the gut microbiota

Significance Our 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. 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.