Comprehensive determination of the microbial composition of the gut microbiota and the relationships with health and disease are major challenges in the 21st century. Metagenomic analysis of the human gut microbiota detects mostly uncultured bacteria. We studied stools from two lean Africans and one obese European, using 212 different culture conditions (microbial culturomics), and tested the colonies by using mass spectrometry and 16S rRNA amplification and sequencing. In parallel, we analysed the same three samples by pyrosequencing 16S rRNA amplicons targeting the V6 region. The 32 500 colonies obtained by culturomics have yielded 340 species of bacteria from seven phyla and 117 genera, including two species from rare phyla (Deinococcus-Thermus and Synergistetes, five fungi, and a giant virus (Senegalvirus). The microbiome identified by culturomics included 174 species never described previously in the human gut, including 31 new species and genera for which the genomes were sequenced, generating c. 10 000 new unknown genes (ORFans), which will help in future molecular studies. Among these, the new species Microvirga massiliensis has the largest bacterial genome so far obtained from a human, and Senegalvirus is the largest virus reported in the human gut. Concurrent metagenomic analysis of the same samples produced 698 phylotypes, including 282 known species, 51 of which overlapped with the microbiome identified by culturomics. Thus, culturomics complements metagenomics by overcoming the depth bias inherent in metagenomic approaches.

Background:Obesity is associated with increased health risk and has been associated with alterations in bacterial gut microbiota, with mainly a reduction in Bacteroidetes, but few data exist at the genus and species level. It has been reported that the Lactobacillus and Bifidobacterium genus representatives may have a critical role in weight regulation as an anti-obesity effect in experimental models and humans, or as a growth-promoter effect in agriculture depending on the strains.Objectives and methods:To confirm reported gut alterations and test whether Lactobacillus or Bifidobacterium species found in the human gut are associated with obesity or lean status, we analyzed the stools of 68 obese and 47 controls targeting Firmicutes, Bacteroidetes, Methanobrevibacter smithii, Lactococcus lactis, Bifidobacterium animalis and seven species of Lactobacillus by quantitative PCR (qPCR) and culture on a Lactobacillus-selective medium.Findings:In qPCR, B. animalis (odds ratio (OR)=0.63; 95% confidence interval (CI) 0.39–1.01; P=0.056) and M. smithii (OR=0.76; 95% CI 0.59–0.97; P=0.03) were associated with normal weight whereas Lactobacillus reuteri (OR=1.79; 95% CI 1.03–3.10; P=0.04) was associated with obesity.Conclusion:The gut microbiota associated with human obesity is depleted in M. smithii. Some Bifidobacterium or Lactobacillus species were associated with normal weight (B. animalis) while others (L. reuteri) were associated with obesity. Therefore, gut microbiota composition at the species level is related to body weight and obesity, which might be of relevance for further studies and the management of obesity. These results must be considered cautiously because it is the first study to date that links specific species of Lactobacillus with obesity in humans.

Background:Genus and species level analysis is the best way to characterize alterations in the human gut microbiota that are associated with obesity, because the clustering of obese and lean microbiotas increases with the taxonomic depth of the analysis. Bifidobacterium genus members have been associated with a lean status, whereas different Lactobacillus species are associated both with a lean and an obese status.Objectives and methods:We analyzed the fecal concentrations of Bacteroidetes, Firmicutes, Methanobrevibacter smithii, the genus Lactobacillus, five other Lactobacillus species previously linked with lean or obese populations, Escherichia coli and Bifidobacterium animalis in 263 individuals, including 134 obese, 38 overweight, 76 lean and 15 anorexic subjects to test for the correlation between bacterial concentration and body mass index (BMI). Of these subjects, 137 were used in our previous study.Findings:Firmicutes were found in >98.5%, Bacteroidetes in 67%, M. smithii in 64%, E. coli in 51%, Lactobacillus species between 17 and 25% and B. animalis in 11% of individuals. The fecal concentration of Lactobacillus reuteri was positively correlated with BMI (coefficient=0.85; 95% confidence interval (CI) 0.12–0.58; P=0.02) in agreement with what was reported for Lactobacillus sakei. As reported, B. animalis (coefficient=−0.84; 95% CI −1.61 to −0.07; P=0.03) and M. smithii (coefficient=−0.43, 95% CI −0.90 to 0.05; P=0.08) were negatively associated with the BMI. Unexpectedly, E. coli was found here for the first time to negatively correlate with the BMI (coefficient=−1.05; 95% CI −1.60 to −0.50; P<0.001).Conclusion:Our findings confirm the specificity of the obese microbiota and emphasize the correlation between the concentration of certain Lactobacillus species and obesity.

Postprandial lipemia, which is one of the main characteristics of the atherogenic dyslipidemia with fasting plasma hypertriglyceridemia, low high-density lipoprotein cholesterol and an increase of small and dense low-density lipoproteins is now considered a causal risk factor for atherosclerotic cardiovascular disease and all-cause mortality. Postprandial lipemia, which is mainly related to the increase in chylomicron production, is frequently elevated in individuals at high cardiovascular risk such as obese or overweight patients, type 2 diabetic patients and subjects with a metabolic syndrome who share an insulin resistant state. It is now well known that chylomicron production and thus postprandial lipemia is highly regulated by many factors such as endogenous factors: circulating factors such as hormones or free fatty acids, genetic variants, circadian rhythms, or exogenous factors: food components, dietary supplements and prescription drugs. In this review, we focused on the effect of nutrients, micronutrients and phytochemicals but also on food structure on chylomicron production and postprandial lipemia.