Four Weeks of Probiotic Supplementation Alters the Metabolic Perturbations Induced by Marathon Running: Insight from Metabolomics.
Jamie N PughMarie M PhelanEva Caamaño-GutiérrezS Andy SparksJames P MortonGraeme L CloseDaniel J OwensPublished in: Metabolites (2021)
Few data are available that describe how probiotics influence systemic metabolism during endurance exercise. Metabolomic profiling of endurance athletes will elucidate mechanisms by which probiotics may confer benefits to the athlete. In this study, twenty-four runners (20 male, 4 female) were block randomised into two groups using a double-blind matched-pairs design according to their most recent Marathon performance. Runners were assigned to 28-days of supplementation with a multi-strain probiotic (PRO) or a placebo (PLB). Following 28-days of supplementation, runners performed a competitive track Marathon race. Venous blood samples and muscle biopsies (vastus lateralis) were collected on the morning of the race and immediately post-race. Samples were subsequently analysed by untargeted 1H-NMR metabolomics. Principal component analysis (PCA) identified a greater difference in the post-Marathon serum metabolome in the PLB group vs. PRO. Univariate tests identified 17 non-overlapped metabolites in PLB, whereas only seven were identified in PRO. By building a PLS-DA model of two components, we revealed combinations of metabolites able to discriminate between PLB and PRO post-Marathon. PCA of muscle biopsies demonstrated no discernible difference post-Marathon between treatment groups. In conclusion, 28-days of probiotic supplementation alters the metabolic perturbations induced by a Marathon. Such findings may be related to maintaining the integrity of the gut during endurance exercise.
Keyphrases
- high intensity
- skeletal muscle
- resistance training
- mass spectrometry
- anti inflammatory
- ms ms
- physical activity
- magnetic resonance
- bacillus subtilis
- ultrasound guided
- high resolution
- study protocol
- electronic health record
- liquid chromatography
- artificial intelligence
- big data
- gas chromatography mass spectrometry
- smoking cessation
- deep learning