Longitudinal gut microbiota in healthy Swedish adults
384 fecal samples from a healthy Swedish population with no clinical evidence of disease, profiled longitudinally over one year by shotgun metagenomics and 16S rRNA sequencing to define normal gut microbiota variation. machine-written summary
384 samples · 384 runs · SE · Age unknown · 2022 · 4.52 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 2,304 sample values (collection date, country, latitude, location region, longitude, subject id) |
| ✓ Abstract / description | 384 sample values (health condition) |
| ○ Full text | read; no usable statement or table · PMC12940132, PMC9213702 |
| ○ 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 |
longitudinal
99 of 101 people sampled more than once (382 samples; median 4, up to 4 per person) · follow-up median 9 mo (max 9 mo) · median interval between samples 3 mo (time from visit codes mapped to the stated schedule). Schedule stated by the source: “repeated sampling over the course of one year, visits coded v1-v4”; stated follow-up 12 mo.
Each row is one person (36 shown of 99); dots are samples at days since that person's first sample.
Genera, mean relative abundance over 353 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 | 384 | 100% | 384 | |||
| health_condition | 384 | 100% | 384 | |||
| subject_id | 384 | 100% | 384 | |||
| collection_date | 384 | 100% | 384 | |||
| detailed_location | 384 | 100% | ||||
| latitude | 384 | 100% | 384 | |||
| location_region | 384 | 100% | 384 | |||
| longitude | 384 | 100% | 384 |
- Genome-scale metabolic modelling of the human gut microbiome reveals changes in the glyoxylate and dicarboxylate metabolism in metabolic disorders. 2022 PMID 35754734 PMC9213702 unsure
- Temporal dynamics of gut biosynthetic gene clusters link persistent colonization and engraftment in fecal microbiota transplantation. 2026 PMID 41741396 PMC12940132 unsure
Archive description
In order to use the microbiota as potential biomarker the definition of a normal microbiota with measurable characteristics needs to be established. Here we longitudinally profiled the fecal microbiota of a normal Swedish population with no clinical evidence of disease using both shotgun metagenomics and 16S rRNA gene sequencing to determine compositional and functional variation over the course of one year. Our analyses confirmed that inter-individual differences are larger than intra-individual variation for the composition of gut microbiota, and we identified gene richness and abundance of Faecalibacteriusm prausnitzii, and Bifidobacterium species as stabilizing factors of the gut microbiota in this population. However, the abundance of different microbial species exhibited different levels of intra-individual variability, which was largest for facultative anaerobes and oxygen tolerant bacteria. These bacteria varied extensively in abundance also in individuals with high compositional stability. Therefore, we conclude that repeated sampling is required to account for the normal intra-individual variation of the gut microbiota and allow a more reliable quantification of microbial biomarkers and suggest that the concept of gut microbiota dysbiosis based on the expansion of rare taxa needs to be updated as these may bloom in normal individuals as well.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of age unknown by sonnet_x2 with confidence 0.75. Assay shotgun_dna.
- host run.scientific_name · “Homo sapiens”
- body site study.description · “fecal microbiota of a normal Swedish population”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMEA7000147 | collection_date | 2016 | R1 | 0.90 | biosample.attribute:collection_date | 2016 |
| SAMEA7000147 | country | SE | R1 | 0.90 | sample.attr.geographic_location_country_and_or_sea | Sweden |
| SAMEA7000147 | health_condition | healthy_control | R4 | 0.50 | study.description | normal Swedish population with no clinical evidence of disease |
| SAMEA7000147 | latitude | 57.7089 | R1 | 0.90 | biosample.attribute:geographic_location_latitude+geographic_location_longitude | 57.70887 11.97456 |
| SAMEA7000147 | location_region | Vaestra Goetaland | R1 | 0.60 | biosample.attribute:geographic_location_latitude+geographic_location_longitude | 57.70887 11.97456 |
| SAMEA7000147 | longitude | 11.9746 | R1 | 0.90 | biosample.attribute:geographic_location_latitude+geographic_location_longitude | 57.70887 11.97456 |
| SAMEA7000147 | subject_id | W0001 | R1 | 0.70 | sample.name_rule:alias | W0001_v1 |
Sequencing
384 runs over 384 samples · mean 4.83 Gbp per run (median 4.52 Gbp, total 1,853.60 Gbp; 384 runs with a base count) · layout PAIRED 384 · platform ILLUMINA 384 · models Illumina HiSeq 2500 (384) · 92% of runs with a Sandpiper profile · first public 2022-01-05
Authors (13)
Proffitt C first · Bidkhori G · Lee S · Tebani A · Mardinoglu A · Uhlen M · Moyes DL · Shoaie S last · Garcia-Guevara F first · Resink T · Clasen F · Uhlén M · Achour A
Downloads
PRJEB38984.csv.gz (10.0 KB) · parquet (83.0 KB) — all 384 samples, every field with route and confidence · PRJEB38984_determinations.csv.gz (17.8 KB) — 2,688 evidence rows