Physical exercise modifies animal metabolism profoundly. Until recently, biochemical investigations related to exercise focused on a small number of biomolecules. In the present study, we used a holistic analytical approach to investigate changes in the human urine metabolome elicited by two exercise sessions differing in the duration of the rest interval between repeated efforts. Twelve men performed three sets of two 80 m maximal runs separated by either 10 s or 1 min of rest. Analysis of pre- and postexercise urine samples by (1)H NMR spectroscopy and subsequent multivariate statistical analysis revealed alterations in the levels of 22 metabolites. Urine samples were safely classified according to exercise protocol even when applying unsupervised methods of statistical analysis. Separation of pre- from postexercise samples was mainly due to lactate, pyruvate, hypoxanthine, compounds of the Krebs cycle, amino acids, and products of branched-chain amino acid (BCAA) catabolism. Separation of the two rest intervals was mainly due to lactate, pyruvate, alanine, compounds of the Krebs cycle, and 2-oxoacids of BCAA, all of which increased more with the shorter interval. Metabonomics provides a powerful methodology to gain insight in metabolic changes induced by specific training protocols and may thus advance our knowledge of exercise biochemistry.

Metabonomics is an established strategy in the exploration of the effects of various stimuli on the metabolic fingerprint of biofluids. Here, we present an application of (1)H NMR-based metabonomics on the field of exercise biochemistry. Fourteen men were assigned to either of two training programs, which lasted 8 weeks and involved sets of 80-m maximal runs separated by either 10 s or 1 min of rest. Analysis of pre- and postexercise serum samples, both at the beginning and end of training, by (1)H NMR spectroscopy and subsequent multivariate statistical techniques revealed alterations in the levels of 18 metabolites. Validated O-PLS models could classify the samples in regard to exercise, the separation being mainly due to lactate, pyruvate, alanine, leucine, valine, isoleucine, arginine/lysine, glycoprotein acetyls, and an unidentified metabolite resonating at 8.17 ppm. Samples were also classified safely with respect to training, the separation being mainly due to lactate, pyruvate, methylguanidine, citrate, glucose, valine, taurine, trimethylamine N-oxide, choline-containing compounds, histidines, acetoacetate/acetone, glycoprotein acetyls, and lipids. Samples could not be classified according to the duration of the rest interval between sprints. Our findings underline the power of metabonomics to offer new insights into the short- and long-term impact of exercise on metabolism.

The delineation of exercise biochemistry by utilizing metabolic fingerprinting has become an established strategy. We present a combined RP-UPLC-MS and (1)H NMR strategy, supplemented by photometric assays, to monitor the response of the human urinary metabolome to short maximal exercise. Seventeen male volunteers performed two identical sprint sessions on separate days, consisting of three 80 m maximal runs. Using univariate and multivariate analyses, we followed the fluctuation of 37 metabolites at 1, 1.5, and 2 h postexercise. 2-Hydroxyisovalerate, 2-hydroxybutyrate, 2-oxoisocaproate, 3-methyl-2-oxovalerate, 3-hydroxyisobutyrate, 2-oxoisovalerate, 3-hydroxybutyrate, 2-hydroxyisobutyrate, alanine, pyruvate, and fumarate increased 1 h postexercise and then returned toward baseline. Lactate and acetate were higher than baseline at 1 and 1.5 h. Hypoxanthine and inosine remained above baseline throughout the postexercise period. Urate decreased at 1 h and increased at 1.5 h before returning to baseline. Valine, isoleucine, succinate, citrate, trimethylamine, trimethylamine N-oxide, tyrosine, and formate decreased at 1 h and/or 1.5 h postexercise and then returned to baseline. Creatinine gradually decreased over the sampling period. Glycine, 4-aminohippurate, and hippurate remained below baseline throughout the postexercise period. Our findings show that even one-half minute of maximal exercise elicited major perturbations in human metabolism, several of which persisted for at least 2 h.

Repeated-sprint training often involves short sprints separated by inadequate recovery intervals. The effects of interval duration on metabolic and performance parameters are unclear. We compared the effects of two training programmes, differing in rest interval duration, on muscle (vastus lateralis) metabolism and sprint performance. Sixteen men trained three times a week for 8 weeks, each training session comprising 2-3 sets of two 80-m sprints. Sprints were separated by 10 s (n = 8) or 1 min (n = 8). Both training programmes improved performance in the 100-, 200-, and 300-m sprints, but the improvement was greater in the 10-s group during the final 100 m of the 200- and 300-m runs. Independent of interval duration, training mitigated the drop of muscle ATP after two 80-m sprints. The drop in phosphocreatine and the increases in glucose-6-phosphate and fructose-6-phosphate after two 80-m sprints were greater in the 10-s group. In conclusion, training with a limited number of repeated short sprints (≤10 s) may be more effective in improving speed maintenance in 200- and 300-m runs when performed with a 1:1 rather than a 1:6 exercise-to-rest ratio. This may be due to a greater activation of glycolysis caused, in part, by the limited resynthesis of phosphocreatine during the very short rest interval.