A study of the effects of exercise on the urinary metabolome using normalisation to individual metabolic output.
ABSTRACT: Aerobic exercise, in spite of its multi-organ benefit and potent effect on the metabolome, has yet to be investigated comprehensively via an untargeted metabolomics technology. We conducted an exploratory untargeted liquid chromatography mass spectrometry study to investigate the effects of a one-h aerobic exercise session in the urine of three physically active males. Individual urine samples were collected over a 37-h protocol (two pre-exercise and eight post-exercise). Raw data were subjected to a variety of normalization techniques, with the most effective measure dividing each metabolite by the sum response of that metabolite for each individual across the 37-h protocol expressed as a percentage. This allowed the metabolite responses to be plotted on a normalised scale. Our results highlight significant metabolites located in the following systems: purine pathway, tryptophan metabolism, carnitine metabolism, cortisol metabolism, androgen metabolism, amino acid oxidation, as well as metabolites from the gastrointestinal microbiome. Many of the significant changes observed in our pilot investigation mirror previous research studies, of various methodological designs, published within the last 15 years, although they have never been reported at the same time in a single study.
Project description:Understanding the metabolic processes in energy metabolism, particularly during fasted exercise, is a growing area of research. Previous work has focused on measuring metabolites pre and post exercise. This can provide information about the final state of energy metabolism in the participants, but it does not show how these processes vary during the exercise and any subsequent post-exercise period. To address this, the work described here took fasted participants and subjected them to an exercise and rest protocol under laboratory settings, which allowed for breath and blood sampling both pre, during and post exercise. Analysis of the data produced from both the physiological measurements and the untargeted metabolomics measurements showed clear switching between glycolytic and ketolytic metabolism, with the liquid chromatography-mass spectrometry (LC-MS) data showing the separate stages of ketolytic metabolism, notably the transport, release and breakdown of long chain fatty acids. Several signals, putatively identified as short peptides, were observed to change in a pattern similar to that of the ketolytic metabolites. This work highlights the power of untargeted metabolomic methods as an investigative tool for exercise science, both to follow known processes in a more complete way and discover possible novel biomarkers.
Project description:Knowledge on metabolites distinguishing the metabolic response to acute physical exercise between fit and less fit individuals could clarify mechanisms and metabolic pathways contributing to the beneficial adaptations to exercise. By analyzing data from the cross-sectional KarMeN (Karlsruhe Metabolomics and Nutrition) study, we characterized the acute effects of a standardized exercise tolerance test on urinary metabolites of 255 healthy women and men. In a second step, we aimed to detect a urinary metabolite pattern associated with the cardiorespiratory fitness (CRF), which was determined by measuring the peak oxygen uptake (VO2peak) during incremental exercise. Spot urine samples were collected pre- and post-exercise and 47 urinary metabolites were identified by nuclear magnetic resonance (NMR) spectroscopy. While the univariate analysis of pre-to-post-exercise differences revealed significant alterations in 37 urinary metabolites, principal component analysis (PCA) did not show a clear separation of the pre- and post-exercise urine samples. Moreover, both bivariate correlation and multiple linear regression analyses revealed only weak relationships between the VO2peak and single urinary metabolites or urinary metabolic pattern, when adjusting for covariates like age, sex, menopausal status, and lean body mass (LBM). Taken as a whole, our results show that several urinary metabolites (e.g., lactate, pyruvate, alanine, and acetate) reflect acute exercise-induced alterations in the human metabolism. However, as neither pre- and post-exercise levels nor the fold changes of urinary metabolites substantially accounted for the variation of the covariate-adjusted VO2peak, our results furthermore indicate that the urinary metabolites identified in this study do not allow to draw conclusions on the individual's physical fitness status. Studies investigating the relationship between the human metabolome and functional variables like the CRF should adjust for confounders like age, sex, menopausal status, and LBM.
Project description:An untargeted metabolomics approach was utilized to determine urinary metabolites that could serve as small-molecule biomarkers for treatment response to standard tuberculosis treatment. However, the majority of metabolites that most accurately distinguished patient samples at the time of diagnosis from those at 1 month after the start of therapy lacked structural identification. The detection of unknown metabolite structures is a well-known limitation of untargeted metabolomics and underscores a need for continued elucidation of novel metabolite structures. In this study, we sought to define the structure of a urine metabolite with an experimentally determined mass of 202.1326 Da, classified as molecular feature (MF) 202.1326. A hypothesized structure of N1-acetylisoputreanine was developed for MF 202.1326 using in silico tools and liquid chromatography-tandem mass spectrometry (LC-MS/MS). In the absence of a commercial standard, synthetic N1-acetylisoputreanine was generated using enzymatic and chemical syntheses, and LC-MS/MS was used to confirm the structure of MF 202.1326 as N1-acetylisoputreanine, a proposed terminal polyamine catabolite that had not been previously detected in biological samples. Further analysis demonstrated that N1-acetylisoputreanine and an alternative form of this metabolite, N1-acetylisoputreanine-γ-lactam, are both present in human urine and are likely end-products of polyamine metabolism.
Project description:Uncoupling protein 3 (UCP3) is highly selectively expressed in skeletal muscle and is known to lower mitochondrial reactive oxygen species and promote fatty acid oxidation; however, the global impact of UCP3 activity on skeletal muscle and whole-body metabolism have not been extensively studied. We utilized untargeted metabolomics to identify novel metabolites that distinguish mice overexpressing UCP3 in muscle, both at rest and after exercise regimens that challenged muscle metabolism, to potentially unmask subtle phenotypes. Male wild-type (WT) and muscle-specific UCP3-overexpressing transgenic (UCP3 Tg) C57BL/6J mice were compared with or without a 5 wk endurance training protocol at rest or after an acute exercise bout (EB). Skeletal muscle, liver, and plasma samples were analyzed by gas chromatography time-of-flight mass spectrometry. Discriminant metabolites were considered if within the top 99th percentile of variable importance measurements obtained from partial least-squares discriminant analysis models. A total of 80 metabolites accurately discriminated UCP3 Tg mice from WT when modeled within a specific exercise condition (i.e., untrained/rested, endurance trained/rested, untrained/EB, and endurance trained/EB). Results revealed that several amino acids and amino acid derivatives in skeletal muscle and plasma of UCP3 Tg mice (e.g., Asp, Glu, Lys, Tyr, Ser, Met) were significantly reduced after an EB; that metabolites associated with skeletal muscle glutathione/Met/Cys metabolism (2-hydroxybutanoic acid, oxoproline, Gly, and Glu) were altered in UCP3 Tg mice across all training and exercise conditions; and that muscle metabolite indices of dehydrogenase activity were increased in UCP3 Tg mice, suggestive of a shift in tissue NADH/NAD+ ratio. The results indicate that mitochondrial UCP3 activity affects metabolism well beyond fatty acid oxidation, regulating biochemical pathways associated with amino acid metabolism and redox status. That select metabolites were altered in liver of UCP3 Tg mice highlights that changes in muscle UCP3 activity can also affect other organ systems, presumably through changes in systemic metabolite trafficking.-Aguer, C., Piccolo, B. D., Fiehn, O., Adams, S. H., Harper, M.-E. A novel amino acid and metabolomics signature in mice overexpressing muscle uncoupling protein 3.
Project description:Annotation and identification of metabolite biomarkers is critical for their biological interpretation in metabolic phenotyping studies, presenting a significant bottleneck in the successful implementation of untargeted metabolomics. Here, a systematic multistep protocol was developed for the purification and de novo structural elucidation of urinary metabolites. The protocol is most suited for instances where structure elucidation and metabolite annotation are critical for the downstream biological interpretation of metabolic phenotyping studies. First, a bulk urine pool was desalted using ion-exchange resins enabling large-scale fractionation using precise iterations of analytical scale chromatography. Primary urine fractions were collected and assembled into a "fraction bank" suitable for long-term laboratory storage. Secondary and tertiary fractionations exploited differences in selectivity across a range of reversed-phase chemistries, achieving the purification of metabolites of interest yielding an amount of material suitable for chemical characterization. To exemplify the application of the systematic workflow in a diverse set of cases, four metabolites with a range of physicochemical properties were selected and purified from urine and subjected to chemical formula and structure elucidation by respective magnetic resonance mass spectrometry (MRMS) and NMR analyses. Their structures were fully assigned as tetrahydropentoxyline, indole-3-acetic-acid-O-glucuronide, p-cresol glucuronide, and pregnanediol-3-glucuronide. Unused effluent was collected, dried, and returned to the fraction bank, demonstrating the viability of the system for repeat use in metabolite annotation with a high degree of efficiency.
Project description:BACKGROUND:It is known that bioenergetics of aerobic and resistance exercise are not the same but both can effectively improve depression. However, it is not clear whether and how different types of exercise can influence depression through the same metabolic regulatory system. Metabolomics provides a way to study the correlation between metabolites and changes in exercise and/or diseases through the quantitative analysis of all metabolites in the organism. The objective of this study was to investigate the effects of aerobic and resistance training on urinary metabolites by metabolomics analysis in a rodent model of depression. METHODS:Male Sprague-Dawley rats were given chronic unpredictable mild stress (CUMS) for eight weeks. The validity of the modeling was assessed by behavioral indices. After four weeks of CUMS, the rats that developed depression were randomly divided into a depression control group, an aerobic training group and a resistance training group. There was also a normal control group. From week 5, the rats in the exercise groups were trained for 30 min per day, five days per week, for four weeks. The urine samples were collected pre and post the training program, and analyzed by proton nuclear magnetic resonance (1H-NMR) spectroscopy. RESULTS:Both types of training improved depression-like behavior in CUMS rats. Compared with normal control, 21 potential biomarkers were identified in the urine of CUMS rats, mainly involved in energy, amino acids and intestinal microbial metabolic pathways. Common responses to the training were found in the two exercise groups that the levels of glutamine, acetone and creatine were significantly recalled (all P<0.05) Aerobic training also resulted in changes in pyruvate and trigonelline, while resistance training modified ?-Oxoglutarate, citric acid, and trimethylamine oxide (all P<0.05). CONCLUSIONS:Aerobic and resistance training resulted in common effects on the metabolic pathways of alanine-aspartate-glutamate, TCA cycle, and butyric acid. Aerobic training also had effects on glycolysis or gluconeogenesis and pyruvate metabolism, while resistance training had additional effect on intestinal microbial metabolism.
Project description:BACKGROUND:Exercise changes the concentrations of many metabolites, which are small molecules (<?1.5 kDa) metabolized by the reactions of human metabolism. In recent years, especially mass spectrometry-based metabolomics methods have allowed researchers to measure up to hundreds of metabolites in a single sample in a non-biased fashion. To summarize human exercise metabolomics studies to date, we conducted a systematic review that reports the results of experiments that found metabolite concentrations changes after a bout of human endurance or resistance exercise. METHODS:We carried out a systematic review following PRISMA guidelines and searched for human metabolomics studies that report metabolite concentrations before and within 24 h after endurance or resistance exercise in blood, urine, or sweat. We then displayed metabolites that significantly changed their concentration in at least two experiments. RESULTS:Twenty-seven studies and 57 experiments matched our search criteria and were analyzed. Within these studies, 196 metabolites changed their concentration significantly within 24 h after exercise in at least two experiments. Human biofluids contain mainly unphosphorylated metabolites as the phosphorylation of metabolites such as ATP, glycolytic intermediates, or nucleotides traps these metabolites within cells. Lactate, pyruvate, TCA cycle intermediates, fatty acids, acylcarnitines, and ketone bodies all typically increase after exercise, whereas bile acids decrease. In contrast, the concentrations of proteinogenic and non-proteinogenic amino acids change in different directions. CONCLUSION:Across different exercise modes and in different subjects, exercise often consistently changes the average concentrations of metabolites that belong to energy metabolism and other branches of metabolism. This dataset is a useful resource for those that wish to study human exercise metabolism.
Project description:Metabolites detectible in human biofluids are attractive biomarkers for the diagnosis of early Lyme disease (ELD), a vector-borne infectious disease. Urine represents an easily obtained clinical sample that can be applied for diagnostic purposes. However, few studies have explored urine for biomarkers of ELD. In this study, metabolomics approaches were applied to evaluate small molecule metabolites in urine from patients with ELD (n?=?14), infectious mononucleosis (n?=?14) and healthy controls (n?=?14). Metabolic biosignatures for ELD versus healthy controls and ELD versus infectious mononucleosis were generated using untargeted metabolomics. Pathway analyses and metabolite identification revealed the dysregulation of several metabolic processes in ELD as compared to healthy controls or mononucleosis, including metabolism of tryptophan. Linear discriminant analyses demonstrated that individual metabolic biosignatures can correctly discriminate ELD from the other patient groups with accuracies of 71 to 100%. These data provide proof-of-concept for use of urine metabolites as biomarkers for diagnostic classification of ELD.
Project description:Gut microbiome plays a vital role in human health. Human fecal and urine metabolome could provide a functional readout of gut microbial metabolism as well as its interaction with host and diet. However, this relationship still needs to be fully characterized. We established an untargeted GC-MS metabolomics method which enabled the detection of 122 and 86 metabolites including amino acids, phenolics, indoles, carbohydrates, sugars and metabolites of microbial origin from fecal and urine samples respectively. 41 compounds were confirmed using external standards. Next, we compared the fecal and urine metabolome of 16 healthy Indian and Chinese adults, ages 22-35 years, using a combined GC-MS and LC-MS approach. We showed dietary habit or ethnicity wise grouping of urine and fecal metabolite profiles of Indian and Chinese adults. Our analysis revealed 53 differentiating metabolites including higher abundance of amino acids and phenolics in Chinese and higher abundance of fatty acids, glycocholic acid, metabolites related to tryptophan metabolism in Indian adults. Correlation analysis showed a strong association of metabolites with gut bacterial profiles of the same subjects in the genus and species level. Thus, our results suggest that gut bacterial compositional changes could be eventually monitored and probed using a metabolomics approach.
Project description:Metabolite annotation and identification are primary challenges in untargeted metabolomics experiments. Rigorous workflows for reliable annotation of mass features with chemical structures or compound classes are needed to enhance the power of untargeted mass spectrometry. High-resolution mass spectrometry considerably improves the confidence in assigning elemental formulas to mass features in comparison to nominal mass spectrometry, and embedding of fragmentation methods enables more reliable metabolite annotations and facilitates metabolite classification. However, the analysis of mass fragmentation spectra can be a time-consuming step and requires expert knowledge. This study demonstrates how characteristic fragmentations, specific to compound classes, can be used to systematically analyze their presence in complex biological extracts like urine that have undergone untargeted mass spectrometry combined with data dependent or targeted fragmentation. Human urine extracts were analyzed using normal phase liquid chromatography (hydrophilic interaction chromatography) coupled to an Ion Trap-Orbitrap hybrid instrument. Subsequently, mass chromatograms and collision-induced dissociation and higher-energy collisional dissociation (HCD) fragments were annotated using the freely available MAGMa software. Acylcarnitines play a central role in energy metabolism by transporting fatty acids into the mitochondrial matrix. By filtering on a combination of a mass fragment and neutral loss designed based on the MAGMa fragment annotations, we were able to classify and annotate 50 acylcarnitines in human urine extracts, based on high-resolution mass spectrometry HCD fragmentation spectra at different energies for all of them. Of these annotated acylcarnitines, 31 are not described in HMDB yet and for only 4 annotated acylcarnitines the fragmentation spectra could be matched to reference spectra. Therefore, we conclude that the use of mass fragmentation filters within the context of untargeted metabolomics experiments is a valuable tool to enhance the annotation of small metabolites.