Jeremiah J. Faith

The Effect of Diet on the Human Gut Microbiome: A Metagenomic Analysis in Humanized Gnotobiotic Mice

A translational medicine pipeline is described where human gut microbial communities and diets are re-created in gnotobiotic mice and the impact on microbe and host is defined using metagenomics. Are You a Man or a Mouse? Answer: Both Comedian Bill Maher targets obese people with his satire almost as often as he does politicians. But clinical obesity is no joke. The World Health Organization estimates the number of obese people worldwide to be 300 million. Add to that the fact that obesity increases one’s risk for a whole stable of serious illnesses—type II diabetes, stroke, and some cancers—and you have one large global disease burden. Scientists and sociologists cite several hypotheses regarding the causes of the obesity epidemic, such as minimal physical exercise, high-fructose corn syrup, and diets of low-cost, large-portion, fat-filled foods. But pinpointing obesity triggers in humans is hard because of uncontrollable genetic, cultural, and environmental variables. Recently, researchers have thrown another element into the mix: the human gut microbiota. A massive number of microbes make the human gut their home. Highly diverse and numbering in the tens of trillions, our microbial companions help shape our human physiology, including effects on metabolism. The extent of their influence is now the subject of intense study in large part because high-capacity, moderately priced DNA sequencing has allowed our microbial communities and their collections of genes (“the microbiome”) to be characterized without having to culture the component organisms. However, this is a challenging business: Studying the factors that shape the assembly and operations of these communities is difficult to do in humans, given our varied genotypes, our difficult-to-document choices of what we eat, and our different environmental exposures. Enter Turnbaugh et al., who add a new tool to the toolbox of translational medicine: mice that only harbor human-derived microbes and that can be reared under conditions where potentially confounding variables encountered in human studies can be controlled. To recreate a model human gut ecosystem, they transplanted human fecal matter into germ-free mice. They show that the transplant was remarkably successful: Recipient animals carried a collection of bacteria that mimicked the human donor’s microbiota. Moreover, the transplanted community could be transmitted from generation to generation of gnotobiotic mice. When these humanized animals were switched from a low-fat, plant-rich diet to a high-fat, high-sugar diet, the microbiota was changed after only 1 day on the junk-food binge. The authors were able to measure microbiome gene content and expression to further understand how the community responded to this diet shift. Like their Homo sapiens counterparts, Western diet–fed humanized mice become obese. Remarkably, this increased adiposity phenotype can be transmitted to other mice, at least for a time, by transplanting their gut microbiota to germ-free recipients. Human microbiome investigators are seeking to extend their descriptive studies. The humanized mice described by Turnbaugh et al. now provide a well-controlled system not only for assaying the functional properties of gut communities harvested from humans with different phenotypes, but also for conducting proof-of-principle “clinical” trials to show how a “host” of factors, including our diets, may influence our microbiota and how in turn our microbiota shapes our health and disease predispositions. Diet and nutritional status are among the most important modifiable determinants of human health. The nutritional value of food is influenced in part by a person’s gut microbial community (microbiota) and its component genes (microbiome). Unraveling the interrelations among diet, the structure and operations of the gut microbiota, and nutrient and energy harvest is confounded by variations in human environmental exposures, microbial ecology, and genotype. To help overcome these problems, we created a well-defined, representative animal model of the human gut ecosystem by transplanting fresh or frozen adult human fecal microbial communities into germ-free C57BL/6J mice. Culture-independent metagenomic analysis of the temporal, spatial, and intergenerational patterns of bacterial colonization showed that these humanized mice were stably and heritably colonized and reproduced much of the bacterial diversity of the donor’s microbiota. Switching from a low-fat, plant polysaccharide–rich diet to a high-fat, high-sugar “Western” diet shifted the structure of the microbiota within a single day, changed the representation of metabolic pathways in the microbiome, and altered microbiome gene expression. Reciprocal transplants involving various combinations of donor and recipient diets revealed that colonization history influences the initial structure of the microbial community but that these effects can be rapidly altered by diet. Humanized mice fed the Western diet have increased adiposity; this trait is transmissible via microbiota transplantation. Humanized gnotobiotic mice will be useful for conducting proof-of-principle “clinical trials” that test the effects of environmental and genetic factors on the gut microbiota and host physiology.

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.

Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing

High-throughput sequencing has revolutionized microbial ecology, but read quality remains a considerable barrier to accurate taxonomy assignment and α-diversity assessment for microbial communities. We demonstrate that high-quality read length and abundance are the primary factors differentiating correct from erroneous reads produced by Illumina GAIIx, HiSeq and MiSeq instruments. We present guidelines for user-defined quality-filtering strategies, enabling efficient extraction of high-quality data and facilitating interpretation of Illumina sequencing results.

The Long-Term Stability of the Human Gut Microbiota

Background Understanding the dynamics and stability of the human gut microbiota is important if its characterization is to play a role in the diagnosis, treatment, and prevention of disease. To characterize stability in related and unrelated individuals and its responsiveness to physiologic change (weight loss), we developed a method for bacterial 16S rRNA amplicon sequencing at high depth with high precision. We also sequenced the genomes of anaerobic bacteria represented in culture collections prepared from fecal samples collected from individuals over time. Methods Low-error amplicon sequencing (LEA-Seq) is a quantitative method based on redundant sequencing of bacterial 16S rRNA genes. A dilute, barcoded, oligonucleotide primer solution is used to create ~150,000 linear PCR extensions of the template DNA. The labeled, bottlenecked linear PCR pool is amplified with exponential PCR, using primers that specifically amplify only the linear PCR molecules. The exponential PCR pool is sequenced at sufficient depth to obtain ~20× coverage. Multiple reads enable the generation of an error-corrected consensus sequence for each barcoded template molecule. LEA-Seq can be used for a variety of other applications. Relationship among time, physiology, and microbiota stability. (A) Stability of fecal microbiota follows a power-law function (n = 37 females sampled over time; >1 week to <5 years). Dashed lines show 95% confidence bounds over 10- and 50-year extrapolations (inset). (B) Microbiota stability is inversely related to the stability of each individual’s body mass index. Results and Discussion LEA-Seq of fecal samples from 37 healthy U.S. adults sampled 2 to 13 times up to 296 weeks apart revealed that they harbored 195 ± 48 bacterial strains, representing 101 ± 27 species. On average, their individual microbiota was remarkably stable, with 60% of strains remaining over the course of 5 years. Stability followed a power law, which, when extrapolated, suggests that most strains in an individual’s intestine are residents for decades (figure, panel A). Members of Bacteroidetes and Actinobacteria are significantly more stable components than the population average. LEA-Seq of four individuals sampled during an 8- to 32-week period during a calorie-restricted dietary study showed that weight stability is a significantly better predictor of microbiota stability than the time interval between samples (figure, panel B). After generating clonally arrayed collections of anaerobic bacteria from frozen fecal samples collected from six weight-stable individuals sampled 7 to 69 weeks apart, we produced draft genome sequences for 534 isolates representing 188 strains and 75 species. A targeted approach focused on Methanobrevibacter smithii isolates from two sets of twin pairs and their mothers and Bacteroides thetaiotaomicron strains from nine donors including sister-sister and mother-daughter pairs. Strains, defined as isolates sharing >96% of their genome content, were maintained over time within an individual and between family members but not between unrelated individuals. Thus, early gut colonizers, such as those acquired from our parents and siblings, have the potential to exert their physiologic, metabolic, and immunologic effects for most, and perhaps all, of our lives. Inheritance Guts We know little about the stability of the constituent microbiota in the human gut or the extent to which the gut microbiota are a potential target for long-term health interventions. Faith et al. (p. 10.1126/science.1237439) analyzed the fecal microbiota of 37 individuals and found that, on average, 60% of bacterial strains remained stable for up to 5 years and many were estimated to remain stable for decades. Low-error sequencing data suggest that initial microbial colonizers of infant guts could persist over the life span of an individual. A low-error 16S ribosomal RNA amplicon sequencing method, in combination with whole-genome sequencing of >500 cultured isolates, was used to characterize bacterial strain composition in the fecal microbiota of 37 U.S. adults sampled for up to 5 years. Microbiota stability followed a power-law function, which when extrapolated suggests that most strains in an individual are residents for decades. Shared strains were recovered from family members but not from unrelated individuals. Sampling of individuals who consumed a monotonous liquid diet for up to 32 weeks indicated that changes in strain composition were better predicted by changes in weight than by differences in sampling interval. This combination of stability and responsiveness to physiologic change confirms the potential of the gut microbiota as a diagnostic tool and therapeutic target.

Extensive personal human gut microbiota culture collections characterized and manipulated in gnotobiotic mice

The proportion of the human gut bacterial community that is recalcitrant to culture remains poorly defined. In this report, we combine high-throughput anaerobic culturing techniques with gnotobiotic animal husbandry and metagenomics to show that the human fecal microbiota consists largely of taxa and predicted functions that are represented in its readily cultured members. When transplanted into gnotobiotic mice, complete and cultured communities exhibit similar colonization dynamics, biogeographical distribution, and responses to dietary perturbations. Moreover, gnotobiotic mice can be used to shape these personalized culture collections to enrich for taxa suited to specific diets. We also demonstrate that thousands of isolates from a single donor can be clonally archived and taxonomically mapped in multiwell format to create personalized microbiota collections. Retrieving components of a microbiota that have coexisted in single donors who have physiologic or disease phenotypes of interest and reuniting them in various combinations in gnotobiotic mice should facilitate preclinical studies designed to determine the degree to which tractable bacterial taxa are able to transmit donor traits or influence host biology.

Organismal, genetic, and transcriptional variation in the deeply sequenced gut microbiomes of identical twins

We deeply sampled the organismal, genetic, and transcriptional diversity in fecal samples collected from a monozygotic (MZ) twin pair and compared the results to 1,095 communities from the gut and other body habitats of related and unrelated individuals. Using a new scheme for noise reduction in pyrosequencing data, we estimated the total diversity of species-level bacterial phylotypes in the 1.2-1.5 million bacterial 16S rRNA reads obtained from each deeply sampled cotwin to be ~800 (35.9%, 49.1% detected in both). A combined 1.1 million read 16S rRNA dataset representing 281 shallowly sequenced fecal samples from 54 twin pairs and their mothers contained an estimated 4,018 species-level phylotypes, with each sample having a unique species assemblage (53.4 ± 0.6% and 50.3 ± 0.5% overlap with the deeply sampled cotwins). Of the 134 phylotypes with a relative abundance of >0.1% in the combined dataset, only 37 appeared in >50% of the samples, with one phylotype in the Lachnospiraceae family present in 99%. Nongut communities had significantly reduced overlap with the deeply sequenced twins’ fecal microbiota (18.3 ± 0.3%, 15.3 ± 0.3%). The MZ cotwins’ fecal DNA was deeply sequenced (3.8-6.3 Gbp/sample) and assembled reads were assigned to 25 genus-level phylogenetic bins. Only 17% of the genes in these bins were shared between the cotwins. Bins exhibited differences in their degree of sequence variation, gene content including the repertoire of carbohydrate active enzymes present within and between twins (e.g., predicted cellulases, dockerins), and transcriptional activities. These results provide an expanded perspective about features that make each of us unique life forms and directions for future characterization of our gut ecosystems.

The Impact of a Consortium of Fermented Milk Strains on the Gut Microbiome of Gnotobiotic Mice and Monozygotic Twins

Metagenomic analyses of gnotobiotic mice and monozygotic twins reveal the effects of eating a popular fermented milk product on their microbiomes. A Yogurt a Day… We all enjoy a tasty yogurt and believe that the bacterial species contained in this type of fermented milk product will keep us healthy. But how much influence do the microbes in these products have on our gut microbiomes and consequently our health, and are these effects generalizable to different human populations consuming different diets? These questions are of concern to regulatory agencies who are increasing pressure on manufacturers to validate the health claims of various foods, including yogurts. McNulty and his colleagues, in an exciting new study, describe a way to evaluate their effects on the human gut microbiome. First, they studied the effects of consuming a popular yogurt on the gut microbiomes of seven healthy adult female identical twin pairs. The bacterial and gene composition, as well as the gene expression patterns, of their gut microbial communities were analyzed before, during, and after consumption of the yogurt. These results were compared to those obtained in gnotobiotic mice that were first reared under conditions where the only microbes they harbored were 15 prominent, sequenced human gut bacterial symbionts, after which time they were exposed to the same 5 bacterial strains as those contained in the yogurt. McNulty and colleagues found during repeated sampling of the gut microbiomes of the twins over a 4-month period that the species and gene content of their gut microbial communities remained stable and were not appreciably perturbed by consuming the yogurt. After exposure of the humanized mice to the five bacterial strains in the fermented milk product, the researchers showed that the mice did not exhibit marked changes in the proportional representation of their human symbiotic bacterial species or genes, mirroring the results seen in the twins. However, analysis of gut bacterial gene expression profiles and of urinary metabolites in these mice disclosed that introducing the fermented milk product strains resulted in marked changes in a number of metabolic pathways, most prominently those related to carbohydrate processing. These latter findings helped direct follow-up studies of the twins’ gut samples where they found similar changes in metabolism as those observed in mice. These findings show that mice containing a sequenced model human gut microbiome can serve as part of a preclinical discovery pipeline designed to identify the effects of existing or new bacterial species with purported health benefits on the properties of the human gut microbiome. Although it remains unclear whether eating a yogurt a day will keep the doctor away, the study by McNulty and his colleagues paves the way for future work to analyze in more detail the direct effects of consuming foods containing bacterial species with potential health benefits on the gut microbiomes of various human populations. Understanding how the human gut microbiota and host are affected by probiotic bacterial strains requires carefully controlled studies in humans and in mouse models of the gut ecosystem where potentially confounding variables that are difficult to control in humans can be constrained. Therefore, we characterized the fecal microbiomes and metatranscriptomes of adult female monozygotic twin pairs through repeated sampling 4 weeks before, 7 weeks during, and 4 weeks after consumption of a commercially available fermented milk product (FMP) containing a consortium of Bifidobacterium animalis subsp. lactis, two strains of Lactobacillus delbrueckii subsp. bulgaricus, Lactococcus lactis subsp. cremoris, and Streptococcus thermophilus. In addition, gnotobiotic mice harboring a 15-species model human gut microbiota whose genomes contain 58,399 known or predicted protein-coding genes were studied before and after gavage with all five sequenced FMP strains. No significant changes in bacterial species composition or in the proportional representation of genes encoding known enzymes were observed in the feces of humans consuming the FMP. Only minimal changes in microbiota configuration were noted in mice after single or repeated gavage with the FMP consortium. However, RNA-Seq analysis of fecal samples and follow-up mass spectrometry of urinary metabolites disclosed that introducing the FMP strains into mice results in significant changes in expression of microbiome-encoded enzymes involved in numerous metabolic pathways, most prominently those related to carbohydrate metabolism. B. animalis subsp. lactis, the dominant persistent member of the FMP consortium in gnotobiotic mice, up-regulates a locus in vivo that is involved in the catabolism of xylooligosaccharides, a class of glycans widely distributed in fruits, vegetables, and other foods, underscoring the importance of these sugars to this bacterial species. The human fecal metatranscriptome exhibited significant changes, confined to the period of FMP consumption, that mirror changes in gnotobiotic mice, including those related to plant polysaccharide metabolism. These experiments illustrate a translational research pipeline for characterizing the effects of FMPs on the human gut microbiome.

Predicting a Human Gut Microbiota’s Response to Diet in Gnotobiotic Mice

Model microbial communities in mouse guts respond quickly and predictably to dietary shifts. The interrelationships between our diets and the structure and operations of our gut microbial communities are poorly understood. A model community of 10 sequenced human gut bacteria was introduced into gnotobiotic mice, and changes in species abundance and microbial gene expression were measured in response to randomized perturbations of four defined ingredients in the host diet. From the responses, we developed a statistical model that predicted over 60% of the variation in species abundance evoked by diet perturbations, and we were able to identify which factors in the diet best explained changes seen for each community member. The approach is generally applicable, as shown by a follow-up study involving diets containing various mixtures of pureed human baby foods.

Reverse-engineering transcription control networks

Microarray technologies, which enable the simultaneous measurement of all RNA transcripts in a cell, have spawned the development of algorithms for reverse-engineering transcription control networks. In this article, we classify the algorithms into two general strategies: physical modeling and influence modeling. We discuss the biological and computational principles underlying each strategy, and provide leading examples of each. We also discuss the practical considerations for developing and applying the various methods.

Many Microbe Microarrays Database: uniformly normalized Affymetrix compendia with structured experimental metadata

Many Microbe Microarrays Database (M3D) is designed to facilitate the analysis and visualization of expression data in compendia compiled from multiple laboratories. M3D contains over a thousand Affymetrix microarrays for Escherichia coli, Saccharomyces cerevisiae and Shewanella oneidensis. The expression data is uniformly normalized to make the data generated by different laboratories and researchers more comparable. To facilitate computational analyses, M3D provides raw data (CEL file) and normalized data downloads of each compendium. In addition, web-based construction, visualization and download of custom datasets are provided to facilitate efficient interrogation of the compendium for more focused analyses. The experimental condition metadata in M3D is human curated with each chemical and growth attribute stored as a structured and computable set of experimental features with consistent naming conventions and units. All versions of the normalized compendia constructed for each species are maintained and accessible in perpetuity to facilitate the future interpretation and comparison of results published on M3D data. M3D is accessible at http://m3d.bu.edu/.