Gut microbiome of Irish cricketers during travel
24 faecal samples from healthy Irish cricketers were collected at baseline and after travel, in a longitudinal study of travel's effect on the gut microbiome. machine-written summary
24 samples · 24 runs · IE · Age unknown · 2018 · 0.95 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 144 sample values (collection date, country, lifestyle, sex, subject id, timepoint) |
| ✓ Abstract / description | 48 sample values (health condition, lifestyle detail) |
| ○ Full text | read; no usable statement or table · PMC11684919, PMC9045144, PMC9926762 |
| ○ 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 |
intervention — arms not resolved
Other administered intervention (see intervention_detail) design observational_with_procedure · population healthy_control · Travel to 2016 Cricket World Cup; baseline vs post-travel sampling
“Baseline and post-travel samples were collected” — bioproject.description (study level; per-sample arms are in the intervention column below)
longitudinalteam — not resolved
4 of 4 people sampled more than once (24 samples; median 6, up to 6 per person) · follow-up median 5 mo (max 5 mo) · median interval between samples 30 d (time from collection dates). Schedule stated by the source: “Baseline sample then post-travel samples at multiple points (post Zambia/Namibia, at home, post Australia, post UAE, post India) for a subset of 4 subjects” (time origin: enrolment).
Each row is one person (4 shown); dots are samples at days since that person's first sample.
4 players of one cricket team (whole cohort) sampled at baseline, at home and after tours.
Genera, mean relative abundance over 9 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 | 24 | 100% | 24 | |||
| health_condition | 24 | 100% | 24 | |||
| subject_id | 24 | 100% | 24 | |||
| collection_date | 24 | 100% | 24 | |||
| lifestyle | 24 | 100% | 24 | |||
| lifestyle_detail | 24 | 100% | 24 | |||
| sex | 24 | 100% | 24 | |||
| timepoint_label | 24 | 100% | 24 |
- Investigation of the Ecological Link between Recurrent Microbial Human Gut Communities and Physical Activity. 2022 PMID 35377222 PMC9045144 unsure
- The human gut microbiome of athletes: metagenomic and metabolic insights. 2023 PMID 36782241 PMC9926762 unsure
- Cataloging metagenome-assembled genomes and microbial genes from the athlete gut microbiome. 2024 PMID 39741946 PMC11684919 unsure
Archive description
The numerous changes and stresses experienced during travel have the potential to impact the gut microbiome. Furthermore, travel has been implicated in the spread of antibiotic resistance genes across continents, while animal models employed to investigate the consequences of dietary changes during travel demonstrated impacts on gut motility and microbiota composition. The possibility of gut microbiome-mediated negative impacts arising from travel, and associated consequences for peak performance, would be of particular concern for elite athletes. To this end, here, the gut microbiome of Irish cricketers during travel was characterised.Faecal samples were collected from male (N=14) and female (N=7) cricket players during the build-up to the 2016 Cricket World Cup. Baseline and post-travel samples were collected from all participants and subjected to 16S rRNA gene sequencing. Additionally, samples from a subset of participants (N=4), who provided samples at all time points, were analysed by shotgun metagenomic sequencing.Analysis revealed reductions in alpha diversity following travel, accompanied by shifts in the taxonomic profile of the gut microbiome. The functional potential of the gut microbiome was also altered following travel, with antibiotic resistance and virulence genes undergoing notable changes. This study identifies periods of extensive travel as instances during which the gut microbiome of elite athletes may be particularly susceptible to disruption.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of age unknown by opus_adjudicated with confidence 0.75. Assay shotgun_dna.
- host run.scientific_name · “Homo sapiens”
- host study.description · “male (N=14) and female (N=7) cricket players”
- body site study.description · “Faecal samples were collected”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMEA4853324 | collection_date | 2015-09-30 | R1 | 0.90 | biosample.attribute:collection_date | 2015-09-30 |
| SAMEA4853324 | country | IE | R1 | 0.90 | sample.attr.geographic_location_country_and_or_sea | Ireland |
| SAMEA4853324 | health_condition | healthy_control | R4 | 0.50 | study.description | gut microbiome of Irish cricketers during travel |
| SAMEA4853324 | lifestyle | athlete | R1 | 0.85 | biosample.attribute:project_name | CricketMET |
| SAMEA4853324 | lifestyle_detail | Irish cricketers (elite athletes) | R4 | 0.45 | ena.study_description | elite athletes |
| SAMEA4853324 | sex | male | R1 | 0.85 | biosample.attribute:host_subject_id | Male player 1 |
| SAMEA4853324 | subject_id | Male player 1 | R1 | 0.85 | sample.attr.host_subject_id | Male player 1 |
| SAMEA4853324 | timepoint_label | baseline | R1 | 0.85 | biosample.attribute:title | Male player 1 baseline shotgun |
| SAMEA4853328 | timepoint_label | post Zambia/Namibia | R1 | 0.70 | sample.name_rule:title | Male player 1 post Zambia/Namibia shotgun |
Sequencing
24 runs over 24 samples · mean 1.07 Gbp per run (median 0.95 Gbp, total 25.68 Gbp; 24 runs with a base count) · layout PAIRED 24 · platform ILLUMINA 24 · models NextSeq 500 (24) · 38% of runs with a Sandpiper profile · first public 2018-10-01
Authors (23)
Tarracchini C first · Fontana F · Lugli GA · Mancabelli L · Alessandri G · Turroni F · Ventura M · Milani C last · Longhi G · Argentini C first · Viappiani A · Anzalone R · Angelini L · Bianchi MG · Taurino G · Bussolati O · van Sinderen D · Wosinska L first · Walsh LH · Walsh CJ · Cotter PD · Guinane CM · O'Sullivan O last
Downloads
PRJEB28338.csv.gz (1.7 KB) · parquet (71.0 KB) — all 24 samples, every field with route and confidence · PRJEB28338_determinations.csv.gz (2.2 KB) — 192 evidence rows