Doris Vandeputte

Population-level analysis of gut microbiome variation

“Normal” for the gut microbiota For the benefit of future clinical studies, it is critical to establish what constitutes a “normal” gut microbiome, if it exists at all. Through fecal samples and questionnaires, Falony et al. and Zhernakova et al. targeted general populations in Belgium and the Netherlands, respectively. Gut microbiota composition correlated with a range of factors including diet, use of medication, red blood cell counts, fecal chromogranin A, and stool consistency. The data give some hints for possible biomarkers of normal gut communities. Science, this issue pp. 560 and 565 Two large-scale studies in Western Europe establish environment-diet-microbe-host interactions. Fecal microbiome variation in the average, healthy population has remained under-investigated. Here, we analyzed two independent, extensively phenotyped cohorts: the Belgian Flemish Gut Flora Project (FGFP; discovery cohort; N = 1106) and the Dutch LifeLines-DEEP study (LLDeep; replication; N = 1135). Integration with global data sets (N combined = 3948) revealed a 14-genera core microbiota, but the 664 identified genera still underexplore total gut diversity. Sixty-nine clinical and questionnaire-based covariates were found associated to microbiota compositional variation with a 92% replication rate. Stool consistency showed the largest effect size, whereas medication explained largest total variance and interacted with other covariate-microbiota associations. Early-life events such as birth mode were not reflected in adult microbiota composition. Finally, we found that proposed disease marker genera associated to host covariates, urging inclusion of the latter in study design.

Stool consistency is strongly associated with gut microbiota richness and composition, enterotypes and bacterial growth rates

Objective The assessment of potentially confounding factors affecting colon microbiota composition is essential to the identification of robust microbiome based disease markers. Here, we investigate the link between gut microbiota variation and stool consistency using Bristol Stool Scale classification, which reflects faecal water content and activity, and is considered a proxy for intestinal colon transit time. Design Through 16S rDNA Illumina profiling of faecal samples of 53 healthy women, we evaluated associations between microbiome richness, Bacteroidetes:Firmicutes ratio, enterotypes, and genus abundance with self-reported, Bristol Stool Scale-based stool consistency. Each sample’s microbiota growth potential was calculated to test whether transit time acts as a selective force on gut bacterial growth rates. Results Stool consistency strongly correlates with all known major microbiome markers. It is negatively correlated with species richness, positively associated to the Bacteroidetes:Firmicutes ratio, and linked to Akkermansia and Methanobrevibacter abundance. Enterotypes are distinctly distributed over the BSS-scores. Based on the correlations between microbiota growth potential and stool consistency scores within both enterotypes, we hypothesise that accelerated transit contributes to colon ecosystem differentiation. While shorter transit times can be linked to increased abundance of fast growing species in Ruminococcaceae-Bacteroides samples, hinting to a washout avoidance strategy of faster replication, this trend is absent in Prevotella-enterotyped individuals. Within this enterotype adherence to host tissue therefore appears to be a more likely bacterial strategy to cope with washout. Conclusions The strength of the associations between stool consistency and species richness, enterotypes and community composition emphasises the crucial importance of stool consistency assessment in gut metagenome-wide association studies.

Quantitative microbiome profiling links gut community variation to microbial load

Current sequencing-based analyses of faecal microbiota quantify microbial taxa and metabolic pathways as fractions of the sample sequence library generated by each analysis. Although these relative approaches permit detection of disease-associated microbiome variation, they are limited in their ability to reveal the interplay between microbiota and host health. Comparative analyses of relative microbiome data cannot provide information about the extent or directionality of changes in taxa abundance or metabolic potential. If microbial load varies substantially between samples, relative profiling will hamper attempts to link microbiome features to quantitative data such as physiological parameters or metabolite concentrations. Saliently, relative approaches ignore the possibility that altered overall microbiota abundance itself could be a key identifier of a disease-associated ecosystem configuration. To enable genuine characterization of host–microbiota interactions, microbiome research must exchange ratios for counts. Here we build a workflow for the quantitative microbiome profiling of faecal material, through parallelization of amplicon sequencing and flow cytometric enumeration of microbial cells. We observe up to tenfold differences in the microbial loads of healthy individuals and relate this variation to enterotype differentiation. We show how microbial abundances underpin both microbiota variation between individuals and covariation with host phenotype. Quantitative profiling bypasses compositionality effects in the reconstruction of gut microbiota interaction networks and reveals that the taxonomic trade-off between Bacteroides and Prevotella is an artefact of relative microbiome analyses. Finally, we identify microbial load as a key driver of observed microbiota alterations in a cohort of patients with Crohn’s disease, here associated with a low-cell-count Bacteroides enterotype (as defined through relative profiling).

Prebiotic inulin-type fructans induce specific changes in the human gut microbiota

Objective Contrary to the long-standing prerequisite of inducing selective (ie, bifidogenic) effects, recent findings suggest that prebiotic interventions lead to ecosystem-wide microbiota shifts. Yet, a comprehensive characterisation of this process is still lacking. Here, we apply 16S rDNA microbiota profiling and matching (gas chromatography mass spectrometry) metabolomics to assess the consequences of inulin fermentation both on the composition of the colon bacterial ecosystem and faecal metabolites profiles. Design Faecal samples collected during a double-blind, randomised, cross-over intervention study set up to assess the effect of inulin consumption on stool frequency in healthy adults with mild constipation were analysed. Faecal microbiota composition and metabolite profiles were linked to the studys clinical outcome as well as to quality-of-life measurements recorded. Results While faecal metabolite profiles were not significantly altered by inulin consumption, our analyses did detect a modest effect on global microbiota composition and specific inulin-induced changes in relative abundances of Anaerostipes, Bilophila and Bifidobacterium were identified. The observed decrease in Bilophila abundances following inulin consumption was associated with both softer stools and a favourable change in constipation-specific quality-of-life measures. Conclusions Ecosystem-wide analysis of the effect of a dietary intervention with prebiotic inulin-type fructans on the colon microbiota revealed that this effect is specifically associated with three genera, one of which (Bilophila) representing a promising novel target for mechanistic research. Trial registration number NCT02548247.

Species–function relationships shape ecological properties of the human gut microbiome

Despite recent progress, the organization and ecological properties of the intestinal microbial ecosystem remain under-investigated. Here, using a manually curated metabolic module framework for (meta-)genomic data analysis, we studied species–function relationships in gut microbial genomes and microbiomes. Half of gut-associated species were found to be generalists regarding overall substrate preference, but we observed significant genus-level metabolic diversification linked to bacterial life strategies. Within each genus, metabolic consistency varied significantly, being low in Firmicutes genera and higher in Bacteroides. Differentiation of fermentable substrate degradation potential contributed to metagenomic functional repertoire variation between individuals, with different enterotypes showing distinct saccharolytic/proteolytic/lipolytic profiles. Finally, we found that module-derived functional redundancy was reduced in the low-richness Bacteroides enterotype, potentially indicating a decreased resilience to perturbation, in line with its frequent association to dysbiosis. These results provide insights into the complex structure of gut microbiome-encoded metabolic properties and emphasize the importance of functional and ecological assessment of gut microbiome variation in clinical studies.

Practical considerations for large-scale gut microbiome studies

Abstract First insights on the human gut microbiome have been gained from medium-sized, cross-sectional studies. However, given the modest portion of explained variance of currently identified covariates and the small effect size of gut microbiota modulation strategies, upscaling seems essential for further discovery and characterisation of the multiple influencing factors and their relative contribution. In order to guide future research projects and standardisation efforts, we here review currently applied collection and preservation methods for gut microbiome research. We discuss aspects such as sample quality, applicable omics techniques, user experience and time and cost efficiency. In addition, we evaluate the protocols of a large-scale microbiome cohort initiative, the Flemish Gut Flora Project, to give an idea of perspectives, and pitfalls of large-scale faecal sampling studies. Although cryopreservation can be regarded as the gold standard, freezing protocols generally require more resources due to cold chain management. However, here we show that much can be gained from an optimised transport chain and sample aliquoting before freezing. Other protocols can be useful as long as they preserve the microbial signature of a sample such that relevant conclusions can be drawn regarding the research question, and the obtained data are stable and reproducible over time.

Water activity does not shape the microbiota in the human colon

We recently reported an association between stool consistency as measured by the Bristol Stool Scale (BSS) and major markers of the gut ecosystem, including microbial richness, enterotypes and bacterial growth rates in 53 healthy women.1 Meanwhile, the link between stool consistency and colon microbiota composition has been confirmed in two large-scale (n>1000) cohorts including individuals of both sexes, different age and varying health statuses.2 ,3 In our original manuscript, we hypothesised on mechanisms that would explain the associations observed. Two potential mechanisms were put forward, namely colon ecosystem differentiation through passage rate variation and reduction of water availability. While the impact of passage rate on ecosystem composition has recently been shown to partially account for BSS-associated microbiota variation,4 the potential correlation with water availability remains unexplored. Water activity (aw) is a dimensionless variable that reflects …

Perspectives and pitfalls of microbiome research through home based fecal sampling: the Flemish Gut Flora Project experience

The set up of large-scale, longitudinally sampled cohorts for microbiome research is logistically challenging as sample quality highly depends on the applied storage conditions. Ideally, fecal material intended for microbiome monitoring needs to be frozen immediately after sampling in order to stop the growth of residing bacteria and to conserve baseline microbial abundances. Effective fecal sampling protocols should not only combine comprehensive collection and storage instructions, but also excel in simplicity and hygiene of sample handling to avoid creating a potential population selection. To meet these criteria, the Flemish Gut Flora Project (FGFP), a large-scale (n>5000) microbiome research project based in Flanders (Belgium), developed a home sampling, aliquotting, and freezing protocol that, in combination with a cold chain collection network, would generate high-quality samples for microbiome research, while at the same time reducing logistic and post-collection analysis expenses. Here we evaluate the FGFP sampling procedure in order to share the lessons learned from this project and improve future fecal sampling methods. We investigate selection bias imposed by the recruitment and check drop out values of the different steps of the sampling procedure. Based on questionnaires and temperature-time data of a subset of the samples we evaluate the cold chain and identify pitfalls of this crucial step in fecal sample collection for microbiome research. Furthermore recommendations to improve fecal sampling user experience are deduced from the responses to a user experience questionnaire and options for better fecal sampling procedures that combine these insights with methods to reduce laboratory efforts are proposed.