We are facing a global metabolic health crisis provoked by an obesity epidemic. Here we report the human gut microbial composition in a population sample of 123 non-obese and 169 obese Danish individuals. We find two groups of individuals that differ by the number of gut microbial genes and thus gut bacterial richness. They contain known and previously unknown bacterial species at different proportions; individuals with a low bacterial richness (23% of the population) are characterized by more marked overall adiposity, insulin resistance and dyslipidaemia and a more pronounced inflammatory phenotype when compared with high bacterial richness individuals. The obese individuals among the lower bacterial richness group also gain more weight over time. Only a few bacterial species are sufficient to distinguish between individuals with high and low bacterial richness, and even between lean and obese participants. Our classifications based on variation in the gut microbiome identify subsets of individuals in the general white adult population who may be at increased risk of progressing to adiposity-associated co-morbidities

Complex gene-environment interactions are considered important in the development of obesity. The composition of the gut microbiota can determine the efficacy of energy harvest from food and changes in dietary composition have been associated with changes in the composition of gut microbial populations. The capacity to explore microbiota composition was markedly improved by the development of metagenomic approaches, which have already allowed production of the first human gut microbial gene catalogue and stratifying individuals by their gut genomic profile into different enterotypes, but the analyses were carried out mainly in non-intervention settings. To investigate the temporal relationships between food intake, gut microbiota and metabolic and inflammatory phenotypes, we conducted diet-induced weight-loss and weight-stabilization interventions in a study sample of 38 obese and 11 overweight individuals. Here we report that individuals with reduced microbial gene richness (40%) present more pronounced dys-metabolism and low-grade inflammation, as observed concomitantly in the accompanying paper. Dietary intervention improves low gene richness and clinical phenotypes, but seems to be less efficient for inflammation variables in individuals with lower gene richness. Low gene richness may therefore have predictive potential for the efficacy of intervention.

The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community And Systems-level INteractive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in vitro. Focusing on metabolic interactions between the diet, gut microbiota, and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention.

Paradoxically, loss of immunoglobulin A (IgA), one of the most abundant antibodies, does not irrevocably lead to severe infections in humans but rather is associated with relatively mild respiratory infections, atopy, and auto immunity. IgA might therefore also play covert roles, not uniquely associated with control of pathogens. We show that human IgA deficiency is not associated with massive quantitative perturbations of gut microbial ecology. Metagenomic analysis highlights an expected pathobiont expansion but a less expected depletion in some typi cally beneficial symbionts. Gut colonization by species usually present in the oropharynx is also reminiscent of spatial microbiota disorganization. IgM only partially rescues IgA deficiency because not all typical IgA targets are efficiently bound by IgM in the intestinal lumen. Together, IgA appears to play a nonredundant role at the fore front of the immune/microbial interface, away from the intestinal barrier, ranging from pathobiont control and regulation of systemic inflammation to preservation of commensal diversity and community networks.

Segmented filamentous bacterium (SFB) is a symbiont that drives postnatal maturation of gut adaptive immune responses. In contrast to nonpathogenic E. coli, SFB stimulated vigorous development of Peyer's patches germinal centers but paradoxically induced only a low frequency of specific immunoglobulin A (IgA)-secreting cells with delayed accumulation of somatic mutations. Moreover, blocking Peyer's patch development abolished IgA responses to E. coli, but not to SFB. Indeed, SFB stimulated the postnatal development of isolated lymphoid follicles and tertiary lymphoid tissue, which substituted for Peyer's patches as inductive sites for intestinal IgA and SFB-specific T helper 17 (Th17) cell responses. Strikingly, in mice depleted of gut organized lymphoid tissue, SFB still induced a substantial but nonspecific intestinal Th17 cell response. These results demonstrate that SFB has the remarkable capacity to induce and stimulate multiple types of intestinal lymphoid tissues that cooperate to generate potent IgA and Th17 cell responses displaying only limited target specificity.