Gut microbiome and exercise in collegiate male athletes, Poland
Shotgun metagenomic sequencing of 232 stool samples from 52 adult men (endurance athletes, strength athletes and non-athletic controls) collected before and after Bruce treadmill and Wingate tests, Gdansk, Poland. machine-written summary
232 samples · 232 runs · Adult · 2023 · 1.48 Gbp / sample
Checked this project's papers and archive records yourself? Mark it human-verified.
what each source gave
| ✓ Sequence archive | 834 sample values (intervention, lifestyle, subject id, timepoint) |
| ○ Abstract / description | read; no usable statement |
| ✓ Full text | 464 sample values (antibiotic exposure, sex) · PMC10880968, PMC12062308 |
| ○ 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 · share metadata |
| – Human verified | not yet checked by a person · I checked this project — verify it |
intervention · arms resolved
54 people have samples in more than one arm.
Exercise / physical-training programme design observational_with_procedure · population healthy_control · Wingate anaerobic test and Bruce treadmill (aerobic) exercise test, pre/post sampling
“subjected to a WAnT test and Bruce test” — bioproject.description (study level; per-sample arms are in the intervention column below)
longitudinal
90 of 104 people sampled more than once (218 samples; median 2, up to 3 per person) · follow-up median 1 d (max 1 d) · median interval between samples 1 d (time from visit codes mapped to the stated schedule). Schedule stated by the source: “stool at T0 (pre-exercise, overnight fast), T1 (same day post-exercise), T2 (next morning), for both Wingate and Bruce tests” (time origin: other).
Each row is one person (36 shown of 90); 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 | 232 | 100% | ||||
| country | 0 | 0% | ||||
| health_condition | 0 | 0% | ||||
| subject_id | 232 | 100% | 232 | |||
| antibiotic_exposure | 232 | 100% | 232 | |||
| intervention | 232 | 100% | 232 | |||
| sex | 232 | 100% | 232 | |||
| timepoint_label | 232 | 100% | 232 | |||
| lifestyle | 138 | 59% | 138 |
- Microbiome features associated with performance measures in athletic and non-athletic individuals: A case-control study. 2024 PMID 38381714 PMC10880968 own_data
- Gut microbiome and blood biomarkers reveal differential responses to aerobic and anaerobic exercise in collegiate men of diverse training backgrounds. 2025 PMID 40341642 PMC12062308 own_data
Archive description
Soft tissue injuries are one of the key determinants of the training process effectiveness. Recent developments and reports in the field of soft tissue injuries prompted us to extend those studies on the gut microbiome (GM) analysis. The role of gut microbiota in health maintaining and better results in the field of sport has already been studied. Furthermore some research underlying changes in microbial diversity after severe injury has been published in last few years. However, there is still lack of knowledge regarding the correlation of microbiota composition with sport specification, clinical features, course and outcomes related to the soft tissue injuries occurring during training. Due to the nature of this relations it is difficult to find information referring to those relationships depending on intensity of physical activity. In this study, we will investigate whether anaerobic exercise and induced by maximal intensity exercises muscle damage alters gut microbial communities and whether there is an association between gut microbiota, inflammation response and iron metabolism. The main aim of the proposed project is a detailed and combined characteristics of bacteria affecting those features by using novel technique (NGS) and correlating them with molecular and biochemical biomarkers. The project aimed to: 1) Demonstrate whether Wingate Anaerobic Test (WAnT) will affect the microbiome and hepcidin concentration; 2) Indicate whether and how skeletal muscle damage induced by maximal intensity exercise influence human microbiome; 3) Show whether WAnT test or Bruce test will induce a higher change of microbiome, iron metabolism and the concentration of inflammation markers; 4) Demonstrate whether Bruce test (aerobic) will cause changes in microbiome concentration and whether these changes will correlate with changes in iron metabolism and inflammation process. 5) Indicate whether circulating free DNA (cfDNA) may be used as a new early-stage biomarker of muscle damage and training overload. In order to achieve objectives of that study, 80 people were recruited and divided into groups with a very strict criteria. They were subjected to a WAnT test and Bruce test (at least 2 weeks later). Blood and stool samples were collected for biochemical, genetic and microbiome analysis before and after tissue-damaging tests in very precisely defined timepoints. Extracted material was checked for a proper quality and quantity. For microbiome analysis the shotgun sequencing was performed using NovaSeq Illumina platform with 2x150 reads. After bioinformatical analysis, all results were analysed statistically in order to look for correlations regarding to the influence of typical exercise (WanT, Bruce test), microbiome diversity, cfDNA level and biochemical data between analysed groups of young men. The measurable effect of this study will be a discovery of relationship between specific adaptations induced by physical training, type of tissue injury and microbiome status among analysed groups of people. In combination with conventional methods for determination of a person’s load during and after physical exercise, data obtained from this study can lead to more accurate understanding of processes happening during and after the exercise, and how biochemical changes in the parameters associated to a physical exercises can effect human’s microbiome status. That can result in a more tailored training program which will stimulate the development of desired bacteria and reduce the risk of soft tissue injuries. This may serve also to identify species helpful for athletic achievement. A better understanding of the nature of these postinjury changes may lead to the ability to intervene in otherwise pathological clinical trajectories.
How this project entered the registry
Classified as human gut / stool shotgun DNA metagenome of adult by curator_audit with confidence 0.57. Assay shotgun_dna.
- host runs.scientific_name · “human gut metagenome”
- host papers[0].abstract · “blood and stool samples were collected”
- body site runs.scientific_name · “human gut metagenome”
- body site papers[0].abstract · “blood and stool samples were collected”
- life stage study.title · “exercise-induced muscle damage”
Evidence examples (one per field × route)
| sample | field | value | route | conf. | source | quote |
|---|---|---|---|---|---|---|
| SAMEA112819304 | antibiotic_exposure | no | R3 | 0.70 | paper.body.methods | Use of any antibiotics, synthetic (nonantibiotic) antimicrobial agents, or any anti-inflammatory drugs in a period |
| SAMEA112819304 | intervention | exercise | R1 | 0.70 | sample.name_rule:description | Bruce_Control_After1 |
| SAMEA112819323 | lifestyle | athlete | R1 | 0.70 | sample.name_rule:description | Bruce_Endurance_After1 |
| SAMEA112819304 | sex | male | R3 | 0.70 | paper.body.methods | a total of 52 men were recruited for this study and assigned to one of |
| SAMEA112819304 | subject_id | PR2005 | R1 | 0.70 | sample.name_rule:title | PR2005B |
| SAMEA112819304 | timepoint_label | Bruce After1 | R1 | 0.70 | sample.name_rule:description | Bruce_Control_After1 |
Sequencing
232 runs over 232 samples · mean 1.64 Gbp per run (median 1.48 Gbp, total 380.60 Gbp; 232 runs with a base count) · layout PAIRED 232 · platform ILLUMINA 232 · models Illumina NovaSeq 6000 (232) · 79% of runs with a Sandpiper profile · first public 2023-03-27 – 2023-06-03
Authors (0)
No author record.
Help complete this project
2 of the 4 core fields are below 50% coverage: country, health_condition. Share metadata
Downloads
PRJEB60692.csv.gz (6.5 KB) · parquet (78.2 KB) — all 232 samples, every field with route and confidence · PRJEB60692_determinations.csv.gz (11.1 KB) — 1,298 evidence rows