The human gut microbiome has profound influences on the host's health largely through its interference with various intestinal functions. As recent studies have suggested diversity in the human gut microbiome among human populations, it will be interesting to analyse how gut microbiome is correlated with geographical, cultural, and traditional differences. The Japanese people are known to have several characteristic features such as eating a variety of traditional foods and exhibiting a low BMI and long life span. In this study, we analysed gut microbiomes of the Japanese by comparing the metagenomic data obtained from 106 Japanese individuals with those from 11 other nations. We found that the composition of the Japanese gut microbiome showed more abundant in the phylum Actinobacteria, in particular in the genus Bifidobacterium, than other nations. Regarding the microbial functions, those of carbohydrate metabolism were overrepresented with a concurrent decrease in those for replication and repair, and cell motility. The remarkable low prevalence of genes for methanogenesis with a significant depletion of the archaeon Methanobrevibacter smithii and enrichment of acetogenesis genes in the Japanese gut microbiome compared with others suggested a difference in the hydrogen metabolism pathway in the gut between them. It thus seems that the gut microbiome of the Japanese is considerably different from those of other populations, which cannot be simply explained by diet alone. We postulate possible existence of hitherto unknown factors contributing to the population-level diversity in human gut microbiomes.

Background: Elucidating the ecological and biological identity of extrachromosomal mobile genetic elements (eMGEs), such as plasmids and bacteriophages, in the human gut remains challenging due to their high complexity and diversity. Results: Here, we show efficient identification of eMGEs as complete circular or linear contigs from PacBio long-read metagenomic data. De novo assembly of PacBio long reads from 12 faecal samples generated 82 eMGE contigs (2.5~666.7-kb), which were classified as 71 plasmids and 11 bacteriophages, including 58 novel plasmids and six bacteriophages, and complete genomes of five diverse crAssphages with terminal direct repeats. In a dataset of 413 gut metagenomes from five countries, many of the identified plasmids were highly abundant and prevalent. The ratio of gut plasmids by our plasmid data is more than twice that in the public database. Plasmids outnumbered bacterial chromosomes three to one on average in this metagenomic dataset. Host prediction suggested that Bacteroidetesassociated plasmids predominated, regardless of microbial abundance. The analysis found several plasmid-enriched functions, such as inorganic ion transport, while antibiotic resistance genes were harboured mostly in low-abundance Proteobacteria-associated plasmids. Conclusions: Overall, long-read metagenomics provided an efficient approach for unravelling the complete structure of human gut eMGEs, particularly plasmids.

Large bowel preparation may cause a substantial change in the gut microbiota and metabolites. Here, we included a bowel prep group and a no-procedure control group and evaluated the effects of bowel prep on the stability of the gut microbiome and metabolome as well as on recovery. Gut microbiota and metabolome compositions were analyzed by 16S rRNA sequencing and capillary electrophoresis time-of-flight mass spectrometry, respectively. Analysis of coefficients at the genus and species level and weighted UniFrac distance showed that, compared with controls, microbiota composition was significantly reduced immediately after the prep but not at 14 days after it. For the gut metabolome profiles, correlation coefficients between before and immediately after the prep were significantly lower than those between before and 14 days after prep and were not significantly different compared with those for between-subject differences. Thirty-two metabolites were significantly changed before and immediately after the prep, but these metabolites recovered within 14 days. In conclusion, bowel preparation has a profound effect on the gut microbiome and metabolome, but the overall composition recovers to baseline within 14 days. To properly conduct studies of the human gut microbiome and metabolome, fecal sampling should be avoided immediately after bowel prep.

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