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PRJEB60692 ERP145757

Gut microbiome and exercise in collegiate male athletes, Poland

The impact of exercise-induced muscle damage, inflammation and oxidative stress on the intestinal microbiota in athletes.

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

Sources
✓Sequence archive 834○Abstract / description✓Full text 464○Supplementary tables–External resources–User contribution–Human verified

Checked this project's papers and archive records yourself? Mark it human-verified.

what each source gave
✓ Sequence archive834 sample values (intervention, lifestyle, subject id, timepoint)
○ Abstract / descriptionread; no usable statement
✓ Full text464 sample values (antibiotic exposure, sex) · PMC10880968, PMC12062308
○ Supplementary tablesfiles read; no table could be matched to the samples
– External resourcesnot covered by the external resources we ingest
– User contributionnothing uploaded yet · share metadata
– Human verifiednot yet checked by a person · I checked this project — verify it
Interventions

intervention · arms resolved

EExercise / physical-training programme: 99 people · 173 samplesexercise 99 people · 173 samplesControl / pre-intervention baseline (sample level only): 59 people · 59 samplesno intervention 59 people · 59 samples
exposed vs. not exposed (observational)

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)

Samples at a glance
Age
adult232
Sex
male232
Body site
primary232
Sequencing depth per sample · this project all projects
all projects, 0–0.03 Gbp: 25,080 samples (4 %)this project, 0–0.03 Gbp: 2 samplesall projects, 0.03–0.1 Gbp: 17,066 samples (3 %)all projects, 0.1–0.3 Gbp: 29,179 samples (5 %)all projects, 0.3–1 Gbp: 47,044 samples (8 %)this project, 0.3–1 Gbp: 21 samplesall projects, 1–3 Gbp: 124,983 samples (22 %)this project, 1–3 Gbp: 196 samplesall projects, 3–10 Gbp: 253,728 samples (44 %)this project, 3–10 Gbp: 13 samplesall projects, 10–30 Gbp: 72,533 samples (13 %)all projects, 30–100 Gbp: 3,024 samples (1 %)all projects, 100–300 Gbp: 106 samples (0 %)all projects, ≥ 300 Gbp: 9 samples (0 %)project median 1.48 Gbp per sample0130Gbp
Sampling design and relatedness

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).

PR1002PR1002: day 0PR1002: day 0PR1002: day 1PR1003PR1003: day 0PR1003: day 0PR1003: day 1PR1004PR1004: day 0PR1004: day 0PR1004: day 1PR1022PR1022: day 0PR1022: day 0PR1022: day 1PR1049PR1049: day 0PR1049: day 0PR1049: day 1PR2003PR2003: day 0PR2003: day 0PR2003: day 1PR2007PR2007: day 0PR2007: day 0PR2007: day 1PR2008PR2008: day 0PR2008: day 0PR2008: day 1PR2009PR2009: day 0PR2009: day 0PR2009: day 1PR2010PR2010: day 0PR2010: day 0PR2010: day 1PR2013PR2013: day 0PR2013: day 0PR2013: day 1PR2014PR2014: day 0PR2014: day 0PR2014: day 1PR2015PR2015: day 0PR2015: day 0PR2015: day 1PR2018PR2018: day 0PR2018: day 0PR2018: day 1PR2020PR2020: day 0PR2020: day 0PR2020: day 1PR2022PR2022: day 0PR2022: day 0PR2022: day 1PR2024PR2024: day 0PR2024: day 0PR2024: day 1PR2026PR2026: day 0PR2026: day 0PR2026: day 1PR2030PR2030: day 0PR2030: day 0PR2030: day 1PR2031PR2031: day 0PR2031: day 0PR2031: day 1PR2032PR2032: day 0PR2032: day 0PR2032: day 1PR2033PR2033: day 0PR2033: day 0PR2033: day 1PR2035PR2035: day 0PR2035: day 0PR2035: day 1PR2036PR2036: day 0PR2036: day 0PR2036: day 1PR2038PR2038: day 0PR2038: day 0PR2038: day 1PR2040PR2040: day 0PR2040: day 0PR2040: day 1PR2042PR2042: day 0PR2042: day 0PR2042: day 1PR2046PR2046: day 0PR2046: day 0PR2046: day 1PR2047PR2047: day 0PR2047: day 0PR2047: day 1PR2052PR2052: day 0PR2052: day 0PR2052: day 1PR2053PR2053: day 0PR2053: day 0PR2053: day 1PR2054PR2054: day 0PR2054: day 0PR2054: day 1PR2056PR2056: day 0PR2056: day 0PR2056: day 1PR2058PR2058: day 0PR2058: day 0PR2058: day 1PR2061PR2061: day 0PR2061: day 0PR2061: day 1PR2065PR2065: day 0PR2065: day 0PR2065: day 10 d0 d0 d1 d1 d

Each row is one person (36 shown of 90); dots are samples at days since that person's first sample.

How longitudinal and relatedness information is derived

Community composition

No Sandpiper profile for this project's samples yet.

Field coverage
fieldsamplescoverageR1R2R3R4
age_category232 100%
country0 0%
health_condition0 0%
subject_id232 100%232
antibiotic_exposure232 100%232
intervention232 100%232
sex232 100%232
timepoint_label232 100%232
lifestyle138 59%138
Papers (2)
  • 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
Details
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)
samplefieldvaluerouteconf.sourcequote
SAMEA112819304antibiotic_exposurenoR30.70paper.body.methodsUse of any antibiotics, synthetic (nonantibiotic) antimicrobial agents, or any anti-inflammatory drugs in a period
SAMEA112819304interventionexerciseR10.70sample.name_rule:descriptionBruce_Control_After1
SAMEA112819323lifestyleathleteR10.70sample.name_rule:descriptionBruce_Endurance_After1
SAMEA112819304sexmaleR30.70paper.body.methodsa total of 52 men were recruited for this study and assigned to one of
SAMEA112819304subject_idPR2005R10.70sample.name_rule:titlePR2005B
SAMEA112819304timepoint_labelBruce After1R10.70sample.name_rule:descriptionBruce_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

Samples (232 · every field this project has values for · hover a cell for its source)
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