Novel Polyfermentor Intestinal Model (PolyFermS) for Controlled Ecological Studies: Validation and Effect of pH

In vitro gut fermentation modeling offers a useful platform for ecological studies of the intestinal microbiota. In this study we describe a novel Polyfermentor Intestinal Model (PolyFermS) designed to compare the effects of different treatments on the same complex gut microbiota. The model operated in conditions of the proximal colon is composed of a first reactor containing fecal microbiota immobilized in gel beads, and used to continuously inoculate a set of parallel second-stage reactors. The PolyFermS model was validated with three independent intestinal fermentations conducted for 38 days with immobilized human fecal microbiota obtained from three child donors. The microbial diversity of reactor effluents was compared to donor feces using the HITChip, a high-density phylogenetic microarray targeting small subunit rRNA sequences of over 1100 phylotypes of the human gastrointestinal tract. Furthermore, the metabolic response to a decrease of pH from 5.7 to 5.5, applied to balance the high fermentative activity in inoculum reactors, was studied. We observed a reproducible development of stable intestinal communities representing major taxonomic bacterial groups at ratios similar to these in feces of healthy donors, a high similarity of microbiota composition produced in second-stage reactors within a model, and a high time stability of microbiota composition and metabolic activity over 38 day culture. For all tested models, the pH-drop of 0.2 units in inoculum reactors enhanced butyrate production at the expense of acetate, but was accompanied by a donor-specific reorganization of the reactor community, suggesting a concerted metabolic adaptation and trigger of community-specific lactate or acetate cross-feeding pathways in response to varying pH. Our data showed that the PolyFermS model allows the stable cultivation of complex intestinal microbiota akin to the fecal donor and can be developed for the direct comparison of different experimental conditions in parallel reactors continuously inoculated with the exact same microbiota.     

Interactions and competition within the microbial community of the human colon: links between diet and health

The microbiota of the human intestinal tract play an important role in health, in particular by mediating many of the effects of diet upon gut health. Surveys of 16S rRNA sequence diversity in the human colon have emphasized the low proportion of sequences that match cultured bacterial species. This may reflect limited recent effort on cultivation rather than inherent unculturability, however, as anaerobic isolation methods can apparently recover a wide range of the diversity found. A combination of information from representative cultures, molecular tools for enumeration and tracking of bacterial metabolites offers the most powerful route to understanding the roles played by different groups of bacteria in the gut ecosystem. Progress is being made for example in defining key functional groups including primary colonizers of insoluble dietary substrates, and major contributors to metabolites such as butyrate that influence the health of the gut mucosa. There is increasing evidence that bacterial populations in the large intestine respond to changes in diet, in particular to the type and quantity of dietary carbohydrate. A general consequence of increased carbohydrate consumption is to reduce the pH of the gut lumen, which is likely to play a major role in determining bacterial metabolism and competition. Oligosaccharides used as dietary prebiotics must inevitably have complex effects upon the bacterial community that include non-target organisms and the consequences of metabolic cross-feeding and changes in the gut environment.     

Understanding the effects of diet on bacterial metabolism in the large intestine

Recent analyses of ribosomal RNA sequence diversity have demonstrated the extent of bacterial diversity in the human colon, and have provided new tools for monitoring changes in the composition of the gut microbial community. There is now an excellent opportunity to correlate ecological niches and metabolic activities with particular phylogenetic groups among the microbiota of the human gut. Bacteria that associate closely with particulate material and surfaces in the gut include specialized primary degraders of insoluble substrates, including resistant starch, plant structural polysaccharides and mucin. Butyrate-producing bacteria found in human faeces belong mainly to the clostridial clusters IV and XIVa. In vitro and in vivo evidence indicates that a group related to Roseburia and Eubacterium rectale plays a major role in mediating the butyrogenic effect of fermentable dietary carbohydrates. Additional cluster XIVa species can convert lactate to butyrate, while some members of the clostridial cluster IX convert lactate to propionate. The metabolic outputs of the gut microbial community depend not only on available substrate, but also on the gut environment, with pH playing a major role. Better understanding of the colonic microbial ecosystem will help to explain and predict the effects of dietary additives, including nondigestible carbohydrates, probiotics and prebiotics.     

Levan Enhances Associated Growth of Bacteroides,Escherichia, Streptococcus and Faecalibacterium in Fecal Microbiota

The role of dietary fiber in supporting healthy gut microbiota and overall well-being of the host has been revealed in several studies. Here, we show the effect of a bacterial polyfructan levan on the growth dynamics and metabolism of fecal microbiota in vitro by using isothermal microcalorimetry. Eleven fecal samples from healthy donors were incubated in phosphate-buffered defined medium with or without levan supplementation and varying presence of amino acids. The generation of heat, changes in pH and microbiota composition, concentrations of produced and consumed metabolites during the growth were determined. The composition of fecal microbiota and profile of metabolites changed in response to substrate (levan and amino acids) availability. The main products of levan metabolism were acetic, lactic, butyric, propionic and succinic acids and carbon dioxide. Associated growth of levan-degrading (e.g. Bacteroides) and butyric acid-producing (e.g. Faecalibacterium) taxa was observed in levan-supplemented media. The study shows that the capacity of levan and possibly also other dietary fibers/prebiotics to modulate the composition and function of colon microbiota can be predicted by using isothermal microcalorimetry of fecal samples linked to metabolite and consortia analyses.     

In Vitro Continuous Fermentation Model (PolyFermS) of the Swine Proximal Colon for Simultaneous Testing on the Same Gut Microbiota

In vitro gut modeling provides a useful platform for a fast and reproducible assessment of treatment-related changes. Currently, pig intestinal fermentation models are mainly batch models with important inherent limitations. In this study we developed a novel in vitro continuous fermentation model, mimicking the porcine proximal colon, which we validated during 54 days of fermentation. This model, based on our recent PolyFermS design, allows comparing different treatment effects on the same microbiota. It is composed of a first-stage inoculum reactor seeded with immobilized fecal swine microbiota and used to constantly inoculate (10% v/v) five second-stage reactors, with all reactors fed with fresh nutritive chyme medium and set to mimic the swine proximal colon. Reactor effluents were analyzed for metabolite concentrations and bacterial composition by HPLC and quantitative PCR, and microbial diversity was assessed by 454 pyrosequencing. The novel PolyFermS featured stable microbial composition, diversity and metabolite production, consistent with bacterial activity reported for swine proximal colon in vivo. The constant inoculation provided by the inoculum reactor generated reproducible microbial ecosystems in all second-stage reactors, allowing the simultaneous investigation and direct comparison of different treatments on the same porcine gut microbiota. Our data demonstrate the unique features of this novel PolyFermS design for the swine proximal colon. The model provides a tool for efficient, reproducible and cost-effective screening of environmental factors, such as dietary additives, on pig colonic fermentation.     

Investigating the biological and clinical significance of human dysbioses

Culture-independent microbiological technologies that interrogate complex microbial populations without prior axenic culture, coupled with high-throughput DNA sequencing, have revolutionized the scale, speed and economics of microbial ecological studies. Their application to the medical realm has led to a highly productive merger of clinical, experimental and environmental microbiology. The functional roles played by members of the human microbiota are being actively explored through experimental manipulation of animal model systems and studies of human populations. In concert, these studies have appreciably expanded our understanding of the composition and dynamics of human-associated microbial communities (microbiota). Of note, several human diseases have been linked to alterations in the composition of resident microbial communities, so-called dysbiosis. However, how changes in microbial communities contribute to disease etiology remains poorly defined. Correlation of microbial composition represents integration of only two datasets (phenotype and microbial composition). This article explores strategies for merging the human microbiome data with multiple additional datasets (e.g. host single nucleotide polymorphisms and host gene expression) and for integrating patient-based data with results from experimental animal models to gain deeper understanding of how host-microbe interactions impact disease.     

Spatial heterogeneity and co-occurrence patterns of human mucosal-associated intestinal microbiota

Human gut microbiota shows high inter-subject variations, but the actual spatial distribution and co-occurrence patterns of gut mucosa microbiota that occur within a healthy human instestinal tract remain poorly understood. In this study, we illustrated a model of this mucosa bacterial communities'' biogeography, based on the largest data set so far, obtained via 454-pyrosequencing of bacterial 16S rDNAs associated with 77 matched biopsy tissue samples taken from terminal ileum, ileocecal valve, ascending colon, transverse colon, descending colon, sigmoid colon and rectum of 11 healthy adult subjects. Borrowing from macro-ecology, we used both Taylor''s power law analysis and phylogeny-based beta-diversity metrics to uncover a highly heterogeneous distribution pattern of mucosa microbial inhabitants along the length of the intestinal tract. We then developed a spatial dispersion model with an R-squared value greater than 0.950 to map out the gut mucosa-associated flora''s non-linear spatial distribution pattern for 51.60% of the 188 most abundant gut bacterial species. Furthermore, spatial co-occurring network analysis of mucosa microbial inhabitants together with occupancy (that is habitat generalists, specialists and opportunist) analyses implies that ecological relationships (both oppositional and symbiotic) between mucosa microbial inhabitants may be important contributors to the observed spatial heterogeneity of mucosa microbiota along the human intestine and may even potentially be associated with mutual cooperation within and functional stability of the gut ecosystem.     

Web of ecological interactions in an experimental gut microbiota

The dynamics of all ecosystems are dictated by intrinsic, density‐dependent mechanisms and by density‐independent environmental forcing. In spite of the importance of the gastrointestinal microbiota in health and disease, the ecology of this system remains largely unknown. Here, we take an ecological approach to gut microbial community analysis, with statistical modelling of time series data from chemostats. This approach removes effects of host forcing, allowing us to describe a network of intrinsic interactions determining the dynamic structure of an experimental gut microbiota. Surprisingly, the main colonization pattern in this simplified model system resembled that of the human infant gut, suggesting a potentially important role of density‐dependent interactions in the early gut microbiota. Knowledge of ecological structures in microbial systems may provide us with a means of controlling such systems by modifying the strength and nature of interactions among microbes and between the microbes and their environment.     

Inferring dynamic signatures of microbes in complex host ecosystems

The human gut microbiota comprise a complex and dynamic ecosystem that profoundly affects host development and physiology. Standard approaches for analyzing time-series data of the microbiota involve computation of measures of ecological community diversity at each time-point, or measures of dissimilarity between pairs of time-points. Although these approaches, which treat data as static snapshots of microbial communities, can identify shifts in overall community structure, they fail to capture the dynamic properties of individual members of the microbiota and their contributions to the underlying time-varying behavior of host ecosystems. To address the limitations of current methods, we present a computational framework that uses continuous-time dynamical models coupled with Bayesian dimensionality adaptation methods to identify time-dependent signatures of individual microbial taxa within a host as well as across multiple hosts. We apply our framework to a publicly available dataset of 16S rRNA gene sequences from stool samples collected over ten months from multiple human subjects, each of whom received repeated courses of oral antibiotics. Using new diversity measures enabled by our framework, we discover groups of both phylogenetically close and distant bacterial taxa that exhibit consensus responses to antibiotic exposure across multiple human subjects. These consensus responses reveal a timeline for equilibration of sub-communities of micro-organisms with distinct physiologies, yielding insights into the successive changes that occur in microbial populations in the human gut after antibiotic treatments. Additionally, our framework leverages microbial signatures shared among human subjects to automatically design optimal experiments to interrogate dynamic properties of the microbiota in new studies. Overall, our approach provides a powerful, general-purpose framework for understanding the dynamic behaviors of complex microbial ecosystems, which we believe will prove instrumental for future studies in this field.     

Effects of lactose on colon microbial community structure and function in a four-stage semi-continuous culture system

A semi-continuous four-channel colon simulator was used to study the effects of lactose for the first time on the growth and fermentation dynamics of colonic microbiota. In six separate simulations, lactose supplementation increased the total SCFA concentration by 3-5 fold as compared with the baseline in the respective vessels. The total bacterial density was inversely correlated with lactic acid production (P = 0.003), while production of butyrate (P = 0.007) and propionate (P = 0.02) correlated with higher numbers of bacteria. A major shift in the microbial community structure in the lactose supplemented vessels was demonstrated by bacterial genomic %G+C-profiling of the total population, where lactose supplementation induced a clearly dominant peak in the bifidobacteria prominent area, %G+C 60-65. The transient shift to increased numbers of bifidobacteria (23-27%) of all bacteria in the first two vessels was also confirmed by the bifidobacteria-specific QPCR-method. In conclusion, lactose produced dramatic changes in microbiota composition and activity as compared with the baseline fermentation.     

Differential Effects of Antibiotic Therapy on the Structure and Function of Human Gut Microbiota

The human intestinal microbiota performs many essential functions for the host. Antimicrobial agents, such as antibiotics (AB), are also known to disturb microbial community equilibrium, thereby having an impact on human physiology. While an increasing number of studies investigate the effects of AB usage on changes in human gut microbiota biodiversity, its functional effects are still poorly understood. We performed a follow-up study to explore the effect of ABs with different modes of action on human gut microbiota composition and function. Four individuals were treated with different antibiotics and samples were taken before, during and after the AB course for all of them. Changes in the total and in the active (growing) microbiota as well as the functional changes were addressed by 16S rRNA gene and metagenomic 454-based pyrosequencing approaches. We have found that the class of antibiotic, particularly its antimicrobial effect and mode of action, played an important role in modulating the gut microbiota composition and function. Furthermore, analysis of the resistome suggested that oscillatory dynamics are not only due to antibiotic-target resistance, but also to fluctuations in the surviving bacterial community. Our results indicated that the effect of AB on the human gut microbiota relates to the interaction of several factors, principally the properties of the antimicrobial agent, and the structure, functions and resistance genes of the microbial community.     

A metabolomic view of how the human gut microbiota impacts the host metabolome using humanized and gnotobiotic mice

Defining the functional status of host-associated microbial ecosystems has proven challenging owing to the vast number of predicted genes within the microbiome and relatively poor understanding of community dynamics and community–host interaction. Metabolomic approaches, in which a large number of small molecule metabolites can be defined in a biological sample, offer a promising avenue to ‘fingerprint'' microbiota functional status. Here, we examined the effects of the human gut microbiota on the fecal and urinary metabolome of a humanized (HUM) mouse using an optimized ultra performance liquid chromatography–mass spectrometry-based method. Differences between HUM and conventional mouse urine and fecal metabolomic profiles support host-specific aspects of the microbiota''s metabolomic contribution, consistent with distinct microbial compositions. Comparison of microbiota composition and metabolome of mice humanized with different human donors revealed that the vast majority of metabolomic features observed in donor samples are produced in the corresponding HUM mice, and individual-specific features suggest ‘personalized'' aspects of functionality can be reconstituted in mice. Feeding the mice a defined, custom diet resulted in modification of the metabolite signatures, illustrating that host diet provides an avenue for altering gut microbiota functionality, which in turn can be monitored via metabolomics. Using a defined model microbiota consisting of one or two species, we show that simplified communities can drive major changes in the host metabolomic profile. Our results demonstrate that metabolomics constitutes a powerful avenue for functional characterization of the intestinal microbiota and its interaction with the host.     

Arabinoxylans and inulin differentially modulate the mucosal and luminal gut microbiota and mucin-degradation in humanized rats

The endogenous gut microbiota affects the host in many ways. Prebiotics should favour beneficial intestinal microbes and thus improve host health. In this study, we investigated how a novel class of potential prebiotic long-chain arabinoxylans (LC-AX) and the well-established prebiotic inulin (IN) modulate the gut microbiota of humanized rats. Six weeks after axenic rats were inoculated with a human faecal microbiota, their colonic microbiota was similar to this inoculum (～ 70%), whereas their caecal microbiota was enriched with Verrucomicrobia and Firmicutes concomitant with lower abundance of Bacteroidetes. Moreover, different Bifidobacterium species colonized the lumen (B. adolescentis) and mucus (B. longum and B. bifidum). Both LC-AX and IN increased SCFA levels and induced a shift from acetate towards health-promoting propionate and butyrate respectively. By applying a high-resolution phylogenetic micro-array (HITChip) at the site of fermentation (caecum), IN and LC-AX were shown to stimulate bacterial groups with known butyrate-producers (Roseburia intestinalis, Eubacterium rectale, Anaerostipes caccae) and bifidobacteria (B. longum) respectively. Prebiotic administration also resulted in lower caecal abundances of the mucin-degrading Akkermansia muciniphila and potentially more mucin production by the host. Both factors might explain the increased caecal mucin levels for LC-AX (threefold) and IN (sixfold). These mucins were degraded along the colon, resulting in high faecal abundances of Akkermansia muciniphila for LC-AX and especially IN-treated rats. Finally, the microbial changes caused an adaptation period for the host with less weight gain, after which the host fine-tuned the interaction with this altered microbiota. Our results demonstrate that next to IN, LC-AX are promising prebiotic compounds by stimulating production of health-promoting metabolites by specific microbes in the proximal regions. Further, prebiotic supplementation shifted mucin degradation to distal regions, where mucin-degraders may produce beneficial metabolites (e.g. propionate by Akkermansia muciniphila), so that prebiotics may potentially improve gut health along the entire length of the intestine.     

Design and Investigation of PolyFermS In Vitro Continuous Fermentation Models Inoculated with Immobilized Fecal Microbiota Mimicking the Elderly Colon

In vitro gut modeling is a useful approach to investigate some factors and mechanisms of the gut microbiota independent of the effects of the host. This study tested the use of immobilized fecal microbiota to develop different designs of continuous colonic fermentation models mimicking elderly gut fermentation. Model 1 was a three-stage fermentation mimicking the proximal, transverse and distal colon. Models 2 and 3 were based on the new PolyFermS platform composed of an inoculum reactor seeded with immobilized fecal microbiota and used to continuously inoculate with the same microbiota different second-stage reactors mounted in parallel. The main gut bacterial groups, microbial diversity and metabolite production were monitored in effluents of all reactors using quantitative PCR, 16S rRNA gene 454-pyrosequencing, and HPLC, respectively. In all models, a diverse microbiota resembling the one tested in donor’s fecal sample was established. Metabolic stability in inoculum reactors seeded with immobilized fecal microbiota was shown for operation times of up to 80 days. A high microbial and metabolic reproducibility was demonstrated for downstream control and experimental reactors of a PolyFermS model. The PolyFermS models tested here are particularly suited to investigate the effects of environmental factors, such as diet and drugs, in a controlled setting with the same microbiota source.     

The influence of Staphylococcus aureus on gut microbial ecology in an in vitro continuous culture human colonic model system

An anaerobic three-stage continuous culture model of the human colon (gut model), which represent different anatomical areas of the large intestine, was used to study the effect of S. aureus infection of the gut on the resident faecal microbiota. Studies on the development of the microbiota in the three vessels were performed and bacteria identified by culture independent fluorescence in situ hybridization (FISH). Furthermore, short chain fatty acids (SCFA), as principal end products of gut bacterial metabolism, were measured along with a quantitative assessment of the predominant microbiota. During steady state conditions, numbers of S. aureus cells stabilised until they were washed out, but populations of indigenous bacteria were transiently altered; thus S. aureus was able to compromise colonisation resistance by the colonic microbiota. Furthermore, the concentration of butyric acid in the vessel representing the proximal colon was significantly decreased by infection. Thus infection by S. aureus appears to be able to alter the overall structure of the human colonic microbiota and the microbial metabolic profiles. This work provides an initial in vitro model to analyse interactions with pathogens.     

Effects of Lactose on Colon Microbial Community Structure and Function in a Four-Stage Semi-Continuous Culture System

A semi-continuous four-channel colon simulator was used to study the effects of lactose for the first time on the growth and fermentation dynamics of colonic microbiota. In six separate simulations, lactose supplementation increased the total SCFA concentration by 3–5 fold as compared with the baseline in the respective vessels. The total bacterial density was inversely correlated with lactic acid production (P=0.003), while production of butyrate (P=0.007) and propionate (P=0.02) correlated with higher numbers of bacteria. A major shift in the microbial community structure in the lactose supplemented vessels was demonstrated by bacterial genomic %G+C-profiling of the total population, where lactose supplementation induced a clearly dominant peak in the bifidobacteria prominent area, %G+C 60–65. The transient shift to increased numbers of bifidobacteria (23–27%) of all bacteria in the first two vessels was also confirmed by the bifidobacteria-specific QPCR-method. In conclusion, lactose produced dramatic changes in microbiota composition and activity as compared with the baseline fermentation.     

Worm burden-dependent disruption of the porcine colon microbiota by Trichuris suis infection

Helminth infection in pigs serves as an excellent model for the study of the interaction between human malnutrition and parasitic infection and could have important implications in human health. We had observed that pigs infected with Trichuris suis for 21 days showed significant changes in the proximal colon microbiota. In this study, interactions between worm burden and severity of disruptions to the microbial composition and metabolic potentials in the porcine proximal colon microbiota were investigated using metagenomic tools. Pigs were infected by a single dose of T. suis eggs for 53 days. Among infected pigs, two cohorts were differentiated that either had adult worms or were worm-free. Infection resulted in a significant change in the abundance of approximately 13% of genera detected in the proximal colon microbiota regardless of worm status, suggesting a relatively persistent change over time in the microbiota due to the initial infection. A significant reduction in the abundance of Fibrobacter and Ruminococcus indicated a change in the fibrolytic capacity of the colon microbiota in T. suis infected pigs. In addition, ∼10% of identified KEGG pathways were affected by infection, including ABC transporters, peptidoglycan biosynthesis, and lipopolysaccharide biosynthesis as well as α-linolenic acid metabolism. Trichuris suis infection modulated host immunity to Campylobacter because there was a 3-fold increase in the relative abundance in the colon microbiota of infected pigs with worms compared to naïve controls, but a 3-fold reduction in worm-free infected pigs compared to controls. The level of pathology observed in infected pigs with worms compared to worm-free infected pigs may relate to the local host response because expression of several Th2-related genes were enhanced in infected pigs with worms versus those worm-free. Our findings provided insight into the dynamics of the proximal colon microbiota in pigs in response to T. suis infection.     

The bacterial community and metabolome dynamics and their interactions modulate fermentation process of whole crop corn silage prepared with or without inoculants

Multi-omics approach was adopted to investigate the modulation of bacterial microbiota and metabolome as well as their interactions in whole crop corn ensiling systems by inoculating homofermentative Lactobacillus plantarum or heterofermentative Lactobacillus buchneri. Inoculations of the two different inoculants resulted in substantial differences in microbial community and metabolic composition as well as their dynamics in ensiled corn. Inoculants also altered the correlations of microbiota in different manners, and various keystone species were identified in corn silages with different treatments. Many metabolites with biofunctional activities like bacteriostatic, antioxidant, central nervous system inhibitory and anti-inflammatory were found in the present silage. A constitutive difference in microbiota dynamics was found for several pathways, which were upregulated by specific taxa in middle stage of fermentation, and widespread associations between metabolites with biofunctions and the species of lactic acid bacteria dominated in silage were observed. Multiple microbial and metabolic structures and dynamics were correlated and affected the fermentation process of the corn ensiling systems. Results of the current study improve our understanding of the complicated biological process underlying silage fermentation and provide a framework to re-evaluate silages with biofunctions, which may contribute to target-based regulation methods to produce functional silage for animal production.     

Deciphering microbial interactions in synthetic human gut microbiome communities

The ecological forces that govern the assembly and stability of the human gut microbiota remain unresolved. We developed a generalizable model‐guided framework to predict higher‐dimensional consortia from time‐resolved measurements of lower‐order assemblages. This method was employed to decipher microbial interactions in a diverse human gut microbiome synthetic community. We show that pairwise interactions are major drivers of multi‐species community dynamics, as opposed to higher‐order interactions. The inferred ecological network exhibits a high proportion of negative and frequent positive interactions. Ecological drivers and responsive recipient species were discovered in the network. Our model demonstrated that a prevalent positive and negative interaction topology enables robust coexistence by implementing a negative feedback loop that balances disparities in monospecies fitness levels. We show that negative interactions could generate history‐dependent responses of initial species proportions that frequently do not originate from bistability. Measurements of extracellular metabolites illuminated the metabolic capabilities of monospecies and potential molecular basis of microbial interactions. In sum, these methods defined the ecological roles of major human‐associated intestinal species and illuminated design principles of microbial communities.     

Use of stable isotopes to measure the metabolic activity of the human intestinal microbiota

The human intestinal microbiota is a complex biological system comprising a vast repertoire of microbes with considerable metabolic activity relevant to both bacterial growth and host health. Greater strides have been made in the analysis of microbial diversity than in the measurement of functional activity, particularly in vivo. Stable isotope probing offers a new approach by coupling measurements of metabolic activity with microbial identification. Using a low-enrichment labeling strategy in vitro, this study has identified metabolically active bacterial groups via magnetic-bead capture methodology and stable isotope ratio analysis. Using five probes (EUB338, Bac303, Bif164, EREC482, and Clep866), changes in the activities of key intestinal microbial groups were successfully measured by exploiting tracers of de novo RNA synthesis. Perturbation of the nutrient source with oligofructose generated changes in the activity of bifidobacteria as expected, but also in the Bacteroides-Prevotella group, the Eubacterium rectale-Clostridium coccoides group, and the Clostridium leptum subgroup. Changes in activity were also observed in response to the medium type. This study suggests that changes in the functional activity of the gut microbiota can be assessed using tracers of de novo nucleic acid synthesis combined with measurement of low isotopic enrichment in 16S rRNA. Such tracers potentially limit substrate bias because they are universally available to bacteria. This low-enrichment labeling approach does not depend on the commercial availability of specific labeled substrates and can be easily translated to in vivo probing experiments of the functional activity of the microbiota in the human gut.