Gut strain engraftment after FMT in US adults, case-control
112 fecal metagenome samples from adult FMT donors and recipients in the USA, used to track donor bacterial strain engraftment post-transplantation in a case-control design. machine-written summary
85 samples · 112 runs · US · Adult · 2021 · 1.03 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 357 sample values (country, health condition, health condition detail, intervention, subject id, timepoint) |
| ○ Abstract / description | read; no usable statement |
| ○ Full text | read; no usable statement or table · PMC10041165, PMC10465488, PMC10821315, PMC11636624, PMC12180181, PMC12547691, PMC12940132, PMC13471986, PMC8993687, PMC9588646 |
| ○ 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 |
Faecal microbiota transplantation · population gi_infection_or_diarrhoea · FMT for recurrent C. difficile; donor strains tracked post-transplant in recipients
“fecal transplant of patients with recurrent Clostridium difficile” — abstract:37644161 (study level; per-sample arms are in the intervention column below)
longitudinal — not resolvedFMT donor → recipient
15 of 23 people sampled more than once (72 samples; median 4, up to 10 per person).
FMT: 6 donors linked to 12 recipients (12 pairs); 1 recipient record inconsistent.
donorrecipient · circles are people (pale = no sequenced sample), arrows run donor → recipient and parent → child, curved lines join twins, partners and siblings, squares are shared settings or families without recorded roles. Shown: 6 linked groups from explicit relations. 23 people in the project overall.
Genera, mean relative abundance over 98 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 | 85 | 100% | ||||
| country | 85 | 100% | 85 | |||
| health_condition | 19 | 22% | 19 | |||
| subject_id | 80 | 94% | 80 | |||
| timepoint_label | 85 | 100% | 85 | |||
| intervention | 69 | 81% | 69 | |||
| health_condition_detail | 19 | 22% | 19 |
- Precise quantification of bacterial strains after fecal microbiota transplantation delineates long-term engraftment and explains outcomes. 2021 PMID 34580445 PMC8993687 own_data
- Human gut microbiota stimulate defined innate immune responses that vary from phylum to strain. 2022 PMID 36099923 PMC9588646 own_data
- Species-specific CD4+ T cells enable prediction of mucosal immune phenotypes from microbiota composition. 2023 PMID 36917674 PMC10041165 own_data
- Combining genotoxic gut bacterial strains increases tumor burden and accelerates onset in a germ-free mouse model of colon carcinogenesis. 2026 PMID 42412611 PMC13471986 own_data
- Identification of donor Bacteroides vulgatus genes encoding proteins that correlate with early colonization following fecal transplant of patients with recurrent Clostridium difficile. 2023 PMID 37644161 PMC10465488 unsure
5 more
- Fecal microbiota transplantation promotes reduction of antimicrobial resistance by strain replacement. 2023 PMID 37910603 PMC10821315
- Gut microbiota strain richness is species specific and affects engraftment. 2025 PMID 39604726 PMC12547691
- Baseline colitogenicity and acute perturbations of gut microbiota in immunotherapy-related colitis. 2025 PMID 39666007 PMC11636624
- Engrafting gut bacteriophages have potential to modulate microbial metabolism in fecal microbiota transplantation. 2025 PMID 40542451 PMC12180181
- Temporal dynamics of gut biosynthetic gene clusters link persistent colonization and engraftment in fecal microbiota transplantation. 2026 PMID 41741396 PMC12940132
Archive description
We isolated bacterial strains from donors who provided their samples for Fecal Transplantation (FMT) to several patients with different diseases. We then tracked these strains in corresponding patients using their fecal metagenomics data and our novel algorithm, to understand bacterial dynamics post FMT. In the accompanying manuscript, we also describe how bacterial strain engraftment in patients post-FMT can predict clinical outcome.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of adult by deterministic_prior with confidence 0.90. Assay shotgun_dna.
- host external_curation.infant_catalog · “infant triage reason_code age_adult_only”
- body site study.title · “and tracking of gut bacterial strains following”
- body site study.description · “their samples for Fecal Transplantation (FMT) to”
- life stage external_curation.infant_catalog · “infant triage reason_code age_adult_only”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMN15803894 | country | US | R1 | 0.90 | sample.attr.geo_loc_name | USA |
| SAMN15803894 | health_condition | healthy_control | R1 | 0.70 | sample.name_rule:DESCRIPTION | Healthy human donor |
| SAMN15803904 | health_condition | gi_infection_or_diarrhoea | R1 | 0.70 | sample.name_rule:description | Patient with rCDI and prior to FMT |
| SAMN15803894 | health_condition_detail | Healthy human donor: DESCRIPTION explicitly labels some rows 'Healthy human donor' (-> healthy_control). The abstract states FMT 'has been su | R1 | 0.70 | sample.name_rule:DESCRIPTION | Healthy human donor |
| SAMN15803904 | health_condition_detail | rCDI | R1 | 0.70 | sample.name_rule:description | Patient with rCDI and prior to FMT |
| SAMN15803904 | intervention | no_intervention | R1 | 0.70 | sample.name_rule:description | Patient with rCDI and prior to FMT |
| SAMN15803894 | subject_id | 1001099 | R1 | 0.70 | sample.name_rule:alias | 1001099B |
| SAMN15803894 | timepoint_label | Used in Figure 1b,c and described in more details in Supplem | R1 | 0.85 | biosample.attribute:used_in_publication | used_in_publication: Used in Figure 1b,c and described in more details in Supplementary Table 3 |
Sequencing
112 runs over 85 samples · mean 2.99 Gbp per run (median 1.03 Gbp, total 335.38 Gbp; 112 runs with a base count) · layout PAIRED 112 · platform ILLUMINA 112 · models Illumina HiSeq 4000 (112) · 88% of runs with a Sandpiper profile · first public 2021-07-12 – 2021-07-16
Authors (104)
Fontana F first · Alessandri G · Tarracchini C · Bianchi MG · Rizzo SM · Mancabelli L · Lugli GA · Argentini C · Vergna LM · Anzalone R · Longhi G · Viappiani A · Taurino G · Chiu M · Turroni F · Bussolati O · van Sinderen D · Milani C · Ventura M last · Kiu R first · Shaw AG · Sim K · Acuna-Gonzalez A · Price CA · Bedwell H · Dreger SA · Fowler WJ · Cornwell E · Pickard D · Belteki G · Malsom J · Phillips S · Young GR · Schofield Z · Alcon-Giner C · Berrington JE · Stewart CJ · Dougan G · Clarke P · Douce G · Robinson SD · Kroll JS · Hall LJ last · Koo H first · Morrow CD last · Angelini L · Chen-Liaw A first · Aggarwala V · Mogno I · Haifer C · Li Z · Eggers J · Helmus D · Hart A · Wehkamp J · Lamousé-Smith ESN · Kerby RL · Rey FE · Colombel JF · Kamm MA · Olle B · Norman JM · Menon R · Watson AR · Crossette E · Terveer EM · Keller JJ · Borody TJ · Grinspan A · Paramsothy S · Kaakoush NO · Dubinsky MC · Faith JJ last · Ji S first · Ahmad F · Peng B · Yang Y · Su M · Zhao X · Vatanen T last · Garcia-Guevara F first · Resink T · Clasen F · Uhlén M · Achour A · Shoaie S last · Plitt T first · Piessevaux A · Rajpal U · Fischer J · Spindler MP · Ruprecht C · Desch AN · Chu G · Jiang Z · Wang J · Gevers D · Pocalyko D · Geis AL · Jobin C · Bachman KE · Sears CL · Britton GJ · San Mateo LR
Downloads
PRJNA637878.csv.gz (3.4 KB) · parquet (73.7 KB) — all 85 samples, every field with route and confidence · PRJNA637878_determinations.csv.gz (3.9 KB) — 357 evidence rows