Gut metagenomes for SCFA metabolic modeling, USA
9 gut metagenome samples from the USA, used to validate microbial community-scale metabolic models predicting individual-specific short-chain fatty acid production; cross-sectional design. machine-written summary
9 samples · 9 runs · US · Age unknown · 2023 · 20.22 Gbp / sample
One study deposited as 2 BioProjects (45 catalog samples together): PRJNA1033794 · PRJNA937304 · show together
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 45 sample values (collection date, country, latitude, location region, longitude) |
| ○ Abstract / description | read; no usable statement |
| ○ Full text | read; no usable statement or table · PMC11841136, PMC12363224 |
| ○ Supplementary tables | files read; no table could be matched to the samples |
| – External resources | not covered by the external resources we ingest |
| – User contribution | nothing uploaded yet |
| – Human verified | not yet checked by a person · I checked this project — verify it |
Genera, mean relative abundance over 7 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 | 0 | 0% | ||||
| country | 9 | 100% | 9 | |||
| health_condition | 0 | 0% | ||||
| subject_id | 0 | 0% | ||||
| collection_date | 9 | 100% | 9 | |||
| detailed_location | 9 | 100% | ||||
| latitude | 9 | 100% | 9 | |||
| location_region | 9 | 100% | 9 | |||
| longitude | 9 | 100% | 9 |
- Microbial community-scale metabolic modelling predicts personalized short-chain fatty acid production profiles in the human gut. 2024 PMID 38914826 PMC11841136 unsure
- Metagenomic estimation of absolute bacterial biomass in the mammalian gut through host-derived read normalization. 2025 PMID 40742180 PMC12363224 unsure
Archive description
This is the data for Study D from the manuscript.</p><p>----</p><p>Microbially-derived short-chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation, and integrity of the intestinal epithelium. However, the production of SCFAs can vary widely between individuals consuming the same diet, with lower levels often associated with disease. A mechanistic understanding of this heterogeneity is lacking. We present a microbial community-scale metabolic modeling (MCMM) approach to predict individual-specific SCFA production profiles. We assess the quantitative accuracy of our MCMMs using in vitro, ex vivo, and in vivo data. Next, we identify associations between MCMM SCFA predictions and a panel of blood-based clinical chemistries in a large human cohort. Finally, we demonstrate how MCMMs can be leveraged to design personalized dietary, prebiotic, and probiotic interventions that optimize SCFA production in the gut. Our results represent an important advance in engineering gut microbiome functional outputs for precision health and nutrition.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of age unknown by sonnet_x2 with confidence 0.80. Assay shotgun_dna.
- host run.scientific_name · “human gut metagenome(9)”
- host run.host_tax_id · “9606”
- body site study.title · “in the human gut”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMN38044495 | collection_date | 2023-06-30 | R1 | 0.90 | biosample.attribute:collection_date | 2023-06-30 |
| SAMN38044495 | country | US | R1 | 0.90 | sample.attr.geo_loc_name | USA |
| SAMN38044495 | latitude | 42.3600 | R1 | 0.90 | biosample.attribute:lat_lon | 42.36 N 71.0941 W |
| SAMN38044495 | location_region | Massachusetts | R1 | 0.60 | biosample.attribute:lat_lon | 42.36 N 71.0941 W |
| SAMN38044495 | longitude | -71.0941 | R1 | 0.90 | biosample.attribute:lat_lon | 42.36 N 71.0941 W |
Sequencing
9 runs over 9 samples · mean 20.33 Gbp per run (median 20.22 Gbp, total 183.01 Gbp; 9 runs with a base count) · layout PAIRED 9 · platform ILLUMINA 9 · models Illumina NovaSeq 6000 (9) · 78% of runs with a Sandpiper profile · first public 2023-11-01
Authors (15)
Quinn-Bohmann N first · Wilmanski T · Sarmiento KR · Levy L · Lampe JW · Gurry T · Rappaport N · Ostrem EM · Venturelli OS · Diener C · Gibbons SM last · Tang G first · Carr AV · Perez C · Ramos Sarmiento K
Downloads
PRJNA1033794.csv.gz (1.1 KB) · parquet (69.5 KB) — all 9 samples, every field with route and confidence · PRJNA1033794_determinations.csv.gz (692 B) — 45 evidence rows