Inter-lab comparison of gut microbiome sequencing, Paris
Cross-sectional study of 30 fecal DNA samples from healthy adults in Paris, France, used to compare gut microbiome profiling results across seven laboratories using metabarcoding or metagenomic sequencing methods. machine-written summary
30 samples · 30 runs · FR · Age unknown · 2023 · 0.42 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 120 sample values (collection date, country, location locality, subject id) |
| ○ Abstract / description | read; no usable statement |
| ✓ Full text | 30 sample values (health condition) · PMC10730622 |
| ○ 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
5 of 5 people sampled more than once (30 samples; median 6, up to 6 per person) · follow-up median 3 mo (max 3 mo) · median interval between samples 3 mo (time from collection dates). Schedule stated by the source: “fecal samples collected at two time points: October 2018 (Sx_1) and January 2019 (Sx_2)” (time origin: baseline).
Each row is one person (5 shown); dots are samples at days since that person's first sample.
No Sandpiper profile for this project's samples yet.
| field | samples | coverage | R1 | R2 | R3 | R4 |
|---|---|---|---|---|---|---|
| age_category | 30 | 100% | ||||
| country | 30 | 100% | 30 | |||
| health_condition | 30 | 100% | 30 | |||
| subject_id | 30 | 100% | 30 | |||
| collection_date | 30 | 100% | 30 | |||
| detailed_location | 30 | 100% | ||||
| location_locality | 30 | 100% | 30 |
- Multicenter evaluation of gut microbiome profiling by next-generation sequencing reveals major biases in partial-length metabarcoding approach. 2023 PMID 38114587 PMC10730622 own_data
Archive description
Next generation sequencing workflows, using either metabarcoding or metagenomic approaches, has massively contributed to expand our knowledge of the human gut microbiota, but methodological bias compromises reproducibility across studies. Where these biases have been quantified within several comparative analysis on their own, none have measured inter-laboratory reproducibility, using similar DNA material. Here, we designed a multicenter study involving seven participating laboratories, dedicated to partial- (P1 to P5), full-length (P6) metabarcoding or metagenomic profiling (MGP) using DNA from a mock microbial community or extracted from 10 fecal samples collected at two time points from 5 donors. Fecal material was collected, and the DNA extracted according to the IHMS protocols. The mock and isolated DNA were then provided to the different laboratories for sequencing. Following sequencing analysis according to laboratories routine pipeline, relative taxonomic-count tables defined at the genus level were provided and analyzed. Large variations in alpha-diversity between laboratories, uncorrelated with sequencing depth, were detected among the profiles. Half of the genera identified by P1 were unique to this partner and two-third of the genera identified by MGP were not detected by P3. Analysis of beta-diversity revealed lower inter-individual variance than inter-laboratories variances. The taxonomic profiles of P5 and P6 were more similar to those of MGP than those obtained by P1, P2, P3 and P4. Re-analysis of the raw sequences obtained by partial metabarcoding profiling, using a single bioinformatics pipeline, harmonizes the description of the bacterial profiles which were more similar to each other, expect for P3, and closer to the profiles obtained by MGP. This highlights the major impact of the bioinformatics pipeline, and primarily the database used for taxonomic annotation. Laboratories need to benchmark and optimize their bioinformatics pipeline to monitor its effectiveness in accurately detecting taxa present in gut microbiota.
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.host_tax_id · “9606”
- body site run.scientific_name · “human gut metagenome”
- body site study.description · “10 fecal samples collected at two time points”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMN32184436 | collection_date | 2018-10-15 | R1 | 0.90 | biosample.attribute:collection_date | 2018-10-15 |
| SAMN32184436 | country | FR | R1 | 0.90 | sample.attr.geo_loc_name | France: Paris |
| SAMN32184436 | health_condition | healthy_control | R3 | 0.70 | paper.fulltext.methods | Five healthy adult subjects (S1–S5) were enrolled |
| SAMN32184436 | location_locality | Paris | R1 | 0.85 | biosample.attribute:geo_loc_name | France: Paris |
| SAMN32184436 | subject_id | S1 | R1 | 0.70 | sample.name_rule:experiment_title | S1 |
Sequencing
30 runs over 30 samples · mean 0.41 Gbp per run (median 0.42 Gbp, total 12.43 Gbp; 30 runs with a base count) · layout SINGLE 30 · platform ION_TORRENT 30 · models Ion Torrent Proton (30) · 0% of runs with a Sandpiper profile · first public 2023-03-09
Authors (5)
Roume H first · Mondot S · Saliou A · Le Fresne-Languille S · Doré J last
Downloads
PRJNA911046.csv.gz (1.5 KB) · parquet (70.0 KB) — all 30 samples, every field with route and confidence · PRJNA911046_determinations.csv.gz (1.6 KB) — 150 evidence rows