Gut microbiota in sepsis vs non-sepsis, Brazil (case-control)
89 stool samples (51 non-sepsis, 38 sepsis) from critically ill patients in Rio Grande do Sul, Brazil, analyzed by 16S rRNA sequencing to compare gut microbiota between sepsis and non-sepsis cases; case-control design. machine-written summary
89 samples · 89 runs · BR · Age unknown · 2026 · 0.16 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 534 sample values (collection date, country, latitude, location region, longitude, subject id) |
| ✓ Abstract / description | 90 sample values (antibiotic exposure, health condition detail) |
| ✓ Full text | 89 sample values (location locality) · PMC12411461 |
| ✓ Supplementary tables | 352 sample values (age, health condition, health condition detail, sex) |
| – 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 |
No Sandpiper profile for this project's samples yet.
| field | samples | coverage | R1 | R2 | R3 | R4 |
|---|---|---|---|---|---|---|
| age_category | 82 | 92% | ||||
| country | 89 | 100% | 89 | |||
| health_condition | 88 | 99% | 88 | |||
| subject_id | 89 | 100% | 89 | |||
| antibiotic_exposure | 89 | 100% | 89 | |||
| collection_date | 89 | 100% | 89 | |||
| detailed_location | 89 | 100% | ||||
| health_condition_detail | 89 | 100% | 88 | 1 | ||
| latitude | 89 | 100% | 89 | |||
| location_locality | 89 | 100% | 89 | |||
| location_region | 89 | 100% | 89 | |||
| longitude | 89 | 100% | 89 | |||
| age_at_collection_days | 88 | 99% | 88 | |||
| sex | 88 | 99% | 88 |
- Microbial diversity and composition in the gut microbiome of patients during systemic inflammatory response syndrome: can we use gut bacteria as potential biomarkers to characterize sepsis? 2025 PMID 40918250 PMC12411461 own_data
Archive description
Critically ill patients, including those with systemic inflammatory response syndrome (SIRS) and sepsis, often show altered gut microbiota due to physiological stress and the use of broad-spectrum antibiotics. Although antibiotics are essential for treating infections, they can disrupt the gut microbial balance, potentially worsening patient outcomes. Understanding these changes may help guide microbiota-based interventions to reduce antibiotic-associated harm. This study aimed to identify specific bacterial taxa that distinguish sepsis from non-sepsis cases. A total of 89 stool samples (51 non-sepsis, 38 sepsis) were analyzed to assess microbial diversity and detect differentially abundant taxa using 16S rRNA gene sequencing.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of age unknown by sonnet_x2 with confidence 0.60. Assay shotgun_dna.
- host run.host_tax_id · “9606”
- body site run.scientific_name · “gut metagenome”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMN48151731 | age_at_collection_days | 22280.2 | R2 | 0.80 | paper.supp.DataSheet1.docx[table2!Age] | R001A: Age=61 |
| SAMN48151731 | antibiotic_exposure | yes | R4 | 0.50 | study.description | use of broad-spectrum antibiotics |
| SAMN48151731 | collection_date | 2022-08-25 | R1 | 0.90 | biosample.attribute:collection_date | 2022-08-25 |
| SAMN48151731 | country | BR | R1 | 0.90 | sample.attr.geo_loc_name | Brazil: Rio Grande do Sul |
| SAMN48151731 | health_condition | other_disease | R2 | 0.80 | paper.supp.DataSheet1.docx[table2!Outcome] | R001A: Outcome=no_sepsis |
| SAMN48151731 | health_condition_detail | non-sepsis SIRS patient | R2 | 0.80 | paper.supp.DataSheet1.docx[table2!Outcome] | R001A: Outcome=no_sepsis |
| SAMN48151739 | health_condition_detail | mixed_case_control: sepsis patients vs non-sepsis (SIRS) patients | R4 | 0.50 | study.description | sepsis from non-sepsis cases |
| SAMN48151731 | latitude | -30.0328 | R1 | 0.90 | biosample.attribute:lat_lon | 30.032778 S 51.23 W |
| SAMN48151731 | location_locality | Porto Alegre | R3 | 0.70 | paper.fulltext.methods | Hospital de Clínicas de Porto Alegre (HCPA) |
| SAMN48151731 | location_region | Rio Grande do Sul | R1 | 0.85 | biosample.attribute:geo_loc_name | Brazil: Rio Grande do Sul |
| SAMN48151731 | longitude | -51.2300 | R1 | 0.90 | biosample.attribute:lat_lon | 30.032778 S 51.23 W |
| SAMN48151731 | sex | female | R2 | 0.80 | paper.supp.DataSheet1.docx[table2!Sex] | R001A: Sex=F |
| SAMN48151731 | subject_id | patient_1 | R1 | 0.85 | biosample.attribute:DESCRIPTION | patient_1 |
Sequencing
89 runs over 89 samples · mean 0.16 Gbp per run (median 0.16 Gbp, total 14.12 Gbp; 89 runs with a base count) · layout PAIRED 89 · platform ILLUMINA 89 · models Illumina MiSeq (89) · 0% of runs with a Sandpiper profile · first public 2026-06-01
Authors (17)
Ramalho Guerra R first · da Silva Fernandes P · von Ameln Lovison O · de Ross Forni G · Silva de Oliveira G · Viana LC · Castro Pereira D · Latosinski Matos W · Melo Silveira Moretti M · Zempulski Volpato F · Giordani L · Orlandi Barth P · Vieceli T · Rodrigues Falci D · Manozzo Boniatti M · Barth AL · Martins AF last
Downloads
PRJNA1255639.csv.gz (4.0 KB) · parquet (76.1 KB) — all 89 samples, every field with route and confidence · PRJNA1255639_determinations.csv.gz (9.5 KB) — 1,065 evidence rows