Japanese adult gut microbiome, cross-sectional study
255 gut microbiome samples from Japanese adults, mostly healthy controls (252) with a few obesity cases (3), in a cross-sectional design. machine-written summary
255 samples · 400 runs · JP · Adult · 2016 · 0.28 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 336 sample values (subject id, timepoint) |
| ✓ Abstract / description | 450 sample values (health condition, health condition detail) |
| ✓ Full text | 989 sample values (antibiotic exposure, collection date, country, location site) · PMC4833420, PMC6005635 |
| ✓ Supplementary tables | 388 sample values (age, bmi, sex, subject id) |
| ✓ External resources | 151 sample values (age, bmi, country, health condition, health condition detail, sex) · from GMrepo v3 |
| – User contribution | nothing uploaded yet |
| – Human verified | not yet checked by a person · I checked this project — verify it |
longitudinal — not resolved
48 of 107 people sampled more than once (196 samples; median 2, up to 12 per person). Schedule stated by the source: “26 individuals sampled twice every 8 weeks; 9 individuals sampled five times every 2 weeks”.
Genera, mean relative abundance over 30 profiled gut samples of this project (Sandpiper SingleM profiles, GTDB R232; low-depth and non-metagenome profiles left out).
| field | samples | coverage | R1 | R2 | R3 | R4 |
|---|---|---|---|---|---|---|
| age_category | 255 | 100% | ||||
| country | 255 | 100% | 31 | 224 | ||
| health_condition | 255 | 100% | 29 | 226 | ||
| subject_id | 255 | 100% | 239 | 16 | ||
| antibiotic_exposure | 255 | 100% | 255 | |||
| collection_date | 255 | 100% | 255 | |||
| detailed_location | 255 | 100% | ||||
| health_condition_detail | 255 | 100% | 31 | 224 | ||
| location_site | 255 | 100% | 255 | |||
| sex | 250 | 98% | 250 | |||
| timepoint_label | 97 | 38% | 97 | |||
| age_at_collection_days | 91 | 36% | 91 | |||
| bmi | 91 | 36% | 91 |
- The gut microbiome of healthy Japanese and its microbial and functional uniqueness. 2016 PMID 26951067 PMC4833420 own_data
- Latent environment allocation of microbial community data. 2018 PMID 29874232 PMC6005635 own_data
- Synergy between Cell Surface Glycosidases and Glycan-Binding Proteins Dictates the Utilization of Specific Beta(1,3)-Glucans by Human Gut Bacteroides. 2020 PMID 32265336 PMC7157763 unsure
- Bifidobacterium response to lactulose ingestion in the gut relies on a solute-binding protein-dependent ABC transporter. 2021 PMID 33972677 PMC8110962 unsure
- Human Gut Faecalibacterium prausnitzii Deploys a Highly Efficient Conserved System To Cross-Feed on β-Mannan-Derived Oligosaccharides. 2021 PMID 34061597 PMC8262883 unsure
5 more
- Diverse events have transferred genes for edible seaweed digestion from marine to human gut bacteria. 2022 PMID 35240043 PMC9096808
- Integrated metagenomics identifies a crucial role for trimethylamine-producing Lachnoclostridium in promoting atherosclerosis. 2022 PMID 35273169 PMC8913745
- 2 Hydroxybutyric Acid-Producing Bacteria in Gut Microbiome and Fusobacterium nucleatum Regulates 2 Hydroxybutyric Acid Level In Vivo. 2023 PMID 36984891 PMC10059959
- The molecular basis of cereal mixed-linkage β-glucan utilization by the human gut bacterium Segatella copri. 2024 PMID 39122003 PMC11418011
- The gut methanotroph Methylocystis intestini modulates intestinal peristalsis and fat metabolism via reducing methane levels. 2025 PMID 41331251 PMC12764784
Archive description
The human gut microbiome has profound influences on the host’s health largely through its inter-ference with various intestinal functions. As recent studies have suggested diversity in the humangut microbiome among human populations, it will be interesting to analyse how gut microbiomeis correlated with geographical, cultural, and traditional differences. The Japanese people areknown to have several characteristic features such as eating a variety of traditional foods and exhibit-ing a low BMI and long life span. In this study, we analysed gut microbiomes of the Japanese by com-paring the metagenomic data obtained from 106 Japanese individuals with those from 11 othernations. We found that the composition of the Japanese gut microbiome showed more abundantin the phylum Actinobacteria, in particular in the genus Bifidobacterium, than other nations. Regard-ing the microbial functions, those of carbohydrate metabolism were overrepresented with a concur-rent decrease in those for replication and repair, and cell motility. The remarkable low prevalence ofgenes for methanogenesis with a significant depletion of the archaeon Methanobrevibacter smithii and en-richment of acetogenesis genes in the Japanese gut microbiome compared with others suggested adifference in the hydrogen metabolism pathway in the gut between them. It thus seems that the gutmicrobiome of the Japanese is considerably different from those of other populations, which cannotbe simply explained by diet alone. We postulate possible existence of hitherto unknown factorscontributing to the population-level diversity in human gut microbiomes.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of adult by sonnet_x2 with confidence 0.68. Assay shotgun_dna.
- host run.host_tax_id · “9606”
- body site study.title · “Metagenomics of Japanese gut microbiomes”
- life stage study.description · “low BMI and long life span”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMD00036191 | age_at_collection_days | 13149 | R2 | 0.85 | paper.supp.supp_dsw002_dsw002supp_tables.xlsx[S1!Age] | 36 |
| SAMD00036349 | age_at_collection_days | 7670.25 | R2 | 0.75 | external.gmrepo source | host_age: 21.0 |
| SAMD00036191 | antibiotic_exposure | no | R3 | 0.70 | paper.fulltext.methods | No subjects were treated with antibiotics |
| SAMD00036191 | bmi | 24.2 | R2 | 0.85 | paper.supp.supp_dsw002_dsw002supp_tables.xlsx[S1!BMI] | 24.2 |
| SAMD00036349 | bmi | 18.8 | R2 | 0.75 | external.gmrepo source | BMI: 18.8 |
| SAMD00036191 | collection_date | 2010/2013 | R3 | 0.70 | paper.fulltext.methods | recruited by Azabu University (Japan) from 2010 to 2013 |
| SAMD00036192 | country | JP | R2 | 0.75 | external.gmrepo source | country: Japanese |
| SAMD00036191 | country | JP | R3 | 0.70 | paper.fulltext.methods | Japanese volunteers |
| SAMD00036192 | health_condition | healthy_control | R2 | 0.75 | external.gmrepo source | phenotype: Health |
| SAMD00036191 | health_condition | healthy_control | R4 | 0.50 | paper.abstract | The gut microbiome of healthy Japanese |
| SAMD00036192 | health_condition_detail | Health | R2 | 0.75 | external.gmrepo source | phenotype: Health |
| SAMD00036191 | health_condition_detail | Healthy Japanese individuals; no disease mentioned | R4 | 0.50 | paper.abstract | The gut microbiome of healthy Japanese |
| SAMD00036191 | location_site | Azabu University | R3 | 0.70 | paper.fulltext.methods | recruited by Azabu University (Japan) from 2010 to 2013 |
| SAMD00036191 | sex | male | R2 | 0.85 | paper.supp.supp_dsw002_dsw002supp_tables.xlsx[S1!Sex] | male |
| SAMD00036349 | sex | female | R2 | 0.75 | external.gmrepo source | sex: Female |
| SAMD00036191 | subject_id | FAKO01 | R1 | 0.70 | sample.name_rule:sample_name | FAKO01 |
| SAMD00036240 | subject_id | FMOR01 | R2 | 0.85 | paper.supp.supp_dsw002_dsw002supp_tables.xlsx[S12!Individual] | 'FMOR01 |
| SAMD00036349 | timepoint_label | S00 | R1 | 0.70 | sample.name_rule:sample_name | apr01S00 |
Sequencing
400 runs over 255 samples · mean 0.76 Gbp per run (median 0.50 Gbp, total 305.06 Gbp; 400 runs with a base count) · layout SINGLE 336, PAIRED 64 · platform ION_TORRENT 177, LS454 159, ILLUMINA 64 · models 454 GS FLX Titanium (97), Ion Torrent PGM (89), Ion Torrent Proton (88), Illumina MiSeq (64), 454 GS FLX+ (62) · 14% of runs with a Sandpiper profile · first public 2016-03-10
Authors (34)
Nishijima S first · Suda W · Oshima K · Kim SW · Hirose Y · Morita H · Hattori M last · Yoshida K first · Hirano R · Sakai Y · Choi M · Sakanaka M · Kurihara S · Iino H · Xiao JZ · Katayama T · Odamaki T last · Qin F first · Li J · Mao T · Feng S · Lai M last · Golisch B first · Cordeiro RL · Fraser ASC · Briggs J · Stewart WA · Van Petegem F · Brumer H last · Zhao Y first · Chen H · Huang J · Chistoserdova L · Yu Z last
Downloads
PRJDB3601.csv.gz (7.6 KB) · parquet (81.0 KB) — all 255 samples, every field with route and confidence · PRJDB3601_determinations.csv.gz (16.9 KB) — 2,314 evidence rows