E-MEXP-740
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ABSTRACT:
PROVIDER: E-MEXP-740 | ExpressionAtlas | 2015-10-22
REPOSITORIES: ExpressionAtlas
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Project description:Purpose. Insulin resistant muscle is resistant to gene expression changes induced by acute exercise. This study was undertaken to identify transcription factors that differentially respond to exercise in insulin resistance. Candidate transcription factors were identified from analysis of 5’-untranslated regions (5’-UTRs) of exercise responsive genes and from analysis of the 5’-UTRs of genes coding for proteins that differ in abundance in insulin resistance. Research design and methods. Muscle biopsies were obtained from lean and obese subjects before and after a single exercise bout. Euglycemic glucose clamps assessed insulin sensitivity. Global proteomics analysis identified differentially abundant proteins. The 5’-UTRs of genes coding for significant proteins were subjected to transcription factor enrichment analysis to identify candidate transcription factors. Q-rt-PCR to determine expression of candidate transcription factors was performed on RNA from resting and post-exercise muscle biopsies; immunoblots quantified protein abundance. Results. Obese subjects were insulin resistant compared to lean but performed exercise at the same intensity. Proteins involved in mitochondrial function, protein targeting and translation, and metabolism were among those significantly different between the groups. Transcription factor enrichment analysis of genes coding for these proteins revealed new candidate transcription factors. Q-rt-PCR analysis of RNA and immunoblot analysis from pre- and post-exercise muscle biopsies revealed several transcription and growth factors that had altered responses to exercise in insulin resistant subjects. Conclusions. These results confirm findings of an association between insulin sensitivity and transcription factor mRNA response to exercise and extend these results to show that obesity also may be a sufficient prerequisite for exercise resistance. Analysis of the muscle proteome together with determination of effects of exercise on expression of transcription factors suggests that abnormal responses of transcription factors to exercise may be responsible for differences in protein abundances in insulin resistant muscle.
2021-09-09 | PXD023354 | Pride
Project description:Context: Exercise training is a plausible model for identification of molecular mechanisms that cause metabolic-related changes in human skeletal muscle. Objective: The goal was to explore the molecular basis of the adaptation of skeletal muscle to exercise training. Design and Intervention: Obese male subjects were subjected to an individualized supervised training program targeted in order to optimize lipid oxidation during 8 weeks. Main Outcome Measures: Primary outcome measures were gene expression profiling of skeletal muscle. Body composition, oral glucose tolerance test, Resting metabolic rate, respiratory quotient, maximal oxygen uptake and metabolic biochemistry were also assessed.
2012-12-10 | GSE40551 | GEO
Project description:To gain insight into the mechanisms by which exercise affects muscle stem cell niche, we subjected young and old mice to aerobic exercise and performed whole transcriptome analysis of muscle cells from these animals.
2023-04-19 | GSE193261 | GEO
Project description:Skeletal muscle plays an important role in the health-promoting effects of exercise training, yet the underlying mechanisms are not fully elucidated. Proteomics of skeletal muscle is challenging due to presence of non-muscle tissues and existence of different fiber types confounding the results. This can be circumvented by analysis of pure fibers; however this requires isolation of fibers from fresh tissues. We developed a workflow enabling proteomics analysis of isolated muscle fibers from freeze-dried muscle biopsies and identified >4000 proteins. We investigated effects of exercise training on the pool of slow and fast muscle fibers. Exercise altered expression of >500 proteins irrespective of fiber type covering several metabolic processes, mainly related to mitochondria. Furthermore, exercise training altered proteins involved in regulation of post-translational modifications, transcription, Ca++ signaling, fat, and glucose metabolism in a fiber type-specific manner. Our data serves as a valuable resource for elucidating molecular mechanisms underlying muscle performance and health. Finally, our workflow offers methodological advancement allowing proteomic analyses of already stored freeze-dried human muscle biopsies.
2020-12-21 | PXD012824 | Pride
Project description:Context: Exercise training is a plausible model for identification of molecular mechanisms that cause metabolic-related changes in human skeletal muscle. Objective: The goal was to explore the molecular basis of the adaptation of skeletal muscle to exercise training. Design and Intervention: Obese male subjects were subjected to an individualized supervised training program targeted in order to optimize lipid oxidation during 8 weeks. Main Outcome Measures: Primary outcome measures were gene expression profiling of skeletal muscle. Body composition, oral glucose tolerance test, Resting metabolic rate, respiratory quotient, maximal oxygen uptake and metabolic biochemistry were also assessed. Overall Design The obese (BMI 30-36) male volunteers (age 32-42) were asked to refrain from vigorous physical activity 48h before presenting to the clinical investigation centre, and ate a weight-maintaining diet consisting of 35% fat, 16% protein, and 49% carbohydrates two days before the experiment. Muscle biopsies of Vastus Lateralis weighing 60–100 mg were obtained using the Bergstrom technique, cleaned and snap-frozen in liquid nitrogen. Resting metabolic rate, respiratory quotient and maximal oxygen uptake were assessed. The subjects were investigated at baseline and after 8 weeks of supervised aerobic exercise training program consisting of daily sessions of 45-60 min of endurance exercise, 5 days a week, at least 48-72h after the last acute exercise bout. Skeletal muscle biopsies were obtained at the beginning and at the end of the protocol. Transcriptome analysis compared 8 subjects before vs. after training using arrays using a common reference design (Cy5 dye was incorporated into all muscle RNA samples, while a reference RNA pool made of the mix of commercial human liver, adipose tissue and skeletal muscle RNA was labelled with Cy3 dye (Applied Biosystems/Ambion, Foster City, USA)( and whole genome 4x44k oligonucleotide arrays (Agilent Technologies).
2012-12-10 | E-GEOD-40551 | biostudies-arrayexpress
Project description:Hypoxic conditions and maximal exercise provide related but distinct energetic stresses for muscle tissue and induce different adaptations in skeletal muscle in mammals. High swim performance fish, including Danio Rerio (Zebrafish), are well-able to tolerate both hypoxia and fast swimming. Expression profiling was performed using microarrays to compare and contrast the adaptations to sustained hypoxia and repeated near maximal exercise in skeletal muscle of adult wild-type Zebrafish.
2023-07-31 | GSE179311 | GEO
Project description:The few investigations on exercise-induced global gene expression responses in human skeletal muscle haves typically focused at one specific mode of exercise and few such studies have implemented control measures. However, interpretation on distinct phenotype regulation necessitate comparison between essentially different modes of exercise and the ability to identify true exercise effects, necessitate implementation of independent non-exercise control subjects. Furthermore, muscle transkriptometranscriptome data made available through previous exercise studies can be difficult to extract and interpret by individuals that are inexperienced with bioinformatic procedures. In a comparative study, we; (1) investigated the human skeletal muscle transcriptome response to differentiated exercise and non-exercise control intervention, and; (2) aimed to develop a straightforward search tool to allow for easy extraction and interpretation of our data. We provide a simple spreadsheet containing transcriptome data allowing other investigators to see how mRNA of their interest behave in skeletal muscle following exercise, both endurance, strength and non-exercise. Our approach, allow investigators easy access to information on genuine transcriptome effects of differentiated exercise, to better aid hyporthesis-driven question in this particular field of research.
2014-11-19 | GSE59088 | GEO
Project description:To gain insight into the mechanisms by which exercise affects the muscle stem cell compartment, we subjected young and old mice to aerobic exercise and performed single cell transcriptome analysis of mononucleated cells from hindlimb muscles of these animals.
2023-04-19 | GSE196361 | GEO
Project description:This file describes the SBML version of the mathematical model in the following journal article: Linking Pulmonary Oxygen Uptake, Muscle Oxygen Utilization and Cellular Metabolism during Exercise, Ann Biomed Eng. 2007 Jun;35(6):956-69. (Pubmed ID: 17380394). This mathematical model simulates oxygen transport and metabolism in skeletal muscle in response to a step change from a warm-up steady state to a higher work rate corresponding to exercise at different levels of intensity: moderate (M), heavy (H) and very heavy (VH). The model parameter values are listed in the tables of this article. The parameter values that are independent of the exercise level are reported in Table 2. The parameter values that depend on the exercise level are reported in Tables 1A, 3 and 4.
The model simulations (Figures 2, 3, 4 and 5) were obtained for a representative subject with a set of parameter values different from those in Table 1A, 3 and 4. In the sbml model, these model parameters are used to simulate exercise at a very heavy (VH) intensity for the representative subject. Additionally, the parameter values needed to simulate exercise at moderate (M) and heavy (H) intensity are reported in the list of parameters of the file. The model simulates dynamics of (1) the concentrations of free (F) and total (T) oxygen concentration in blood (CFcap, CTcap) and tissue (CFtis, CTtis), Adenosine Triphosphate (ATP), Adenosine Diphosphate (ADP), Phosphocreatine (PCr) and Creatine (Cr); (2) the metabolic flux of oxidative phosphorylation, creatine kinase and ATPase; (3) the oxygen uptake in blood and oxygen transport rate from blood to tissue during exercise. The simulation also computes muscle oxygen saturation (StO2m) and relative muscle oxygen saturation (RStO2m) in order to compare simulated and experimental responses of human muscle oxygenation during exercise.
The model was successfully tested with Roadrunner of the Systems Biology Workbench (SBW). The model simulations obtained with Roadrunner match those obtained with the mathematical model represented in Fortran and Matlab for relative and absolute tolerance smaller than 10-7.
To allow for simulations at varying levels of exercise, the parameter exercise_level was introduced. A value of 1 means medium, 2 heavy and 3 very heavy exercise. Setting this parameter assigns the parameters Vmax, KatpaseE, dQMm and tauQm with the relevant parameters. The warmup steady state is influenced by the parameter changes for this representative subject and the model has to be brought into steady state after each change of exercise level.
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Nov��re N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2009-10-16 | BIOMD0000000248 | BioModels
Project description:The few investigations on exercise-induced global gene expression responses in human skeletal muscle haves typically focused at one specific mode of exercise and few such studies have implemented control measures. However, interpretation on distinct phenotype regulation necessitate comparison between essentially different modes of exercise and the ability to identify true exercise effects, necessitate implementation of independent non-exercise control subjects. Furthermore, muscle transkriptometranscriptome data made available through previous exercise studies can be difficult to extract and interpret by individuals that are inexperienced with bioinformatic procedures. In a comparative study, we; (1) investigated the human skeletal muscle transcriptome response to differentiated exercise and non-exercise control intervention, and; (2) aimed to develop a straightforward search tool to allow for easy extraction and interpretation of our data. We provide a simple spreadsheet containing transcriptome data allowing other investigators to see how mRNA of their interest behave in skeletal muscle following exercise, both endurance, strength and non-exercise. Our approach, allow investigators easy access to information on genuine transcriptome effects of differentiated exercise, to better aid hyporthesis-driven question in this particular field of research. 18 subjects were divided into 3 groups, performing 12 weeks of Endurance or Strength training or no training. Biopsies for microarray were take before (Pre) and 2½ and 5 hours after the last training session. Isolated RNA from these biopsies were then measured with the Affymetrix Human Gene 1.0 ST arrays.
2014-11-19 | E-GEOD-59088 | biostudies-arrayexpress