Project description:White blood cells (WBCs) express tens of thousands of genes. Their expression levels are modified by genetic and external factors. The purpose of the present study was to investigate the effects of acute exercise on gene expression profiles (GEPs) of WBCs and to identify suitable genes which may serve as surrogate markers for monitoring exercise and training load. Five male probands performed an exhaustive treadmill test (ET) at 80% of their VO2max, and a moderate treadmill test (MT) at 60% VO2max for exactly the same time one to two week later. White blood cells (WBCs) were isolated by the erythrocyte lysis method. Gene expression profiles were measured using the Affymetrix GeneChipÂ® technology. After scaling, normalisation, and filtering groupwise and pairwise comparisons of gene expression intensities were performed and validated by real-time PCR. We found 450 genes up-regulated and 150 down-regulated (> 1.5-fold change; ANOVA with Benjamini-Hochberg correction for multiple testing, p<0.05) upon exhaustive exercise. Analysis of mean expression levels after MT showed that the extent of up- and down-regulation was workload dependent. The genes for the stress proteins HSPA1A, HSPH1 and the matrix metalloproteinase MMP-9 showed the most prominent increases whereas the mRNA concentrations of the YES1 oncogene (YES1), of CD160 (BY55), and of a member of the mitochondrial electron transport chain (ATP5s) were most strongly reduced. Remarkably, we could largely reproduce the data from a previous report by Connolly et al. (01) even though we used considerably different methodology. After acute exercise the genes with increased expression levels were highly significantly associated with the gene ontology terms heat-shock proteins, apoptosis and inflammation. The results demonstrate that gene expression changes in WBCs can reflect intensity and duration of exercise. Further analysis is needed to confirm the applicability of expression fingerprints as useful tools for monitoring exercise and training loads in order to avoid training associated health risks. Experiment Overall Design: Five healthy male probands executed an exhaustive treadmill test (80% VO2max) until individual exhaustion. One week later they repeated the test at 60% VO2max for the same time (moderate test). Blood samples (9ml) were drawn before and one hour past the tests. Erythrocytes were lysed and RNA was isolated from the white blood cells. RNA was processed and hybridised on U133A 2.0 Affyetrix GeneChips. Samples were grouped and gene expression changes were detected via multiple algorithms included in GeneSpring 7.2 (Agilent). Experiment Overall Design: Three groups were build from the twenty samples. All ten pre exercise samples were grouped together as the pre test" group. The other two groups contained five samples related to the "exhaustive test" or the "moderate test". TTest in cobination with multiple testing corrections, principal component analysis and hierarchical clstering were used to scan for gene expression profiles induced through the different exercise conditions.

Project description:MiRNAs are essential mediators of many biological processes. The aim of this study was to investigate the dynamics of miRNA-mRNA regulatory networks during exercise and subsequent recovery period. Here we monitored the transcriptome changes by microarray analysis of the whole blood of eight highly trained athletes after 30 min of moderate exercise followed by 30 min and 60 min of recovery period. We combined expression profiling and bioinformatics and analysed metabolic pathways enriched with differentially expressed mRNAs and then mRNAs which are known to be validated targets of differentially expressed miRNAs. Finally we revealed four dynamically regulated networks comprising differentially expressed miRNAs and their known target mRNAs with anti-correlated expression profiles over time. The data suggest that hsa-miR-21-5p regulated TGFBR3, PDGFD and PPM1L mRNAs. Hsa-miR-24-2-5p was likely to be responsible for MYC and KCNJ2 genes and hsa-miR-27a-5p for ST3GAL6. The targets of hsa-miR-181a-5p included ROPN1L and SLC37A3. All these mRNAs are involved in processes highly relevant to exercise response, including immune function, apoptosis, membrane traffic of proteins and transcription regulation. We have identified four miRNA-mRNA networks dynamically regulated following exercise. This work is the first study to monitor miRNAs and mRNAs in parallel into recovery period. The results provide a novel insight into the regulatory role of miRNAs in stress adaptation. Each subject performed a treadmill test with an incremental step protocol until exhaustion. Blood samples were taken from the antecubital vein using indwelling catheter before (T1), immediately after ramp test to exaustion (T2) and after 30 min of recovery (T3). Two weeks later, athletes participated in the main exercise, consisting of running at 80% VO2 peak for 30 min on a treadmill. Blood samples were taken from the antecubital vein using indwelling catheter before (T4), immediately after running at 80% VO2 peak for 30 min on a treadmill (T5), after 30 min (T6) and 60 min (T7) of recovery.

Project description:White blood cells (WBCs) express tens of thousands of genes. Their expression levels are modified by genetic and external factors. The purpose of the present study was to investigate the effects of acute exercise on gene expression profiles (GEPs) of WBCs and to identify suitable genes which may serve as surrogate markers for monitoring exercise and training load. Five male probands performed an exhaustive treadmill test (ET) at 80% of their VO2max, and a moderate treadmill test (MT) at 60% VO2max for exactly the same time one to two week later. White blood cells (WBCs) were isolated by the erythrocyte lysis method. Gene expression profiles were measured using the Affymetrix GeneChip® technology. After scaling, normalisation, and filtering groupwise and pairwise comparisons of gene expression intensities were performed and validated by real-time PCR. We found 450 genes up-regulated and 150 down-regulated (> 1.5-fold change; ANOVA with Benjamini-Hochberg correction for multiple testing, p<0.05) upon exhaustive exercise. Analysis of mean expression levels after MT showed that the extent of up- and down-regulation was workload dependent. The genes for the stress proteins HSPA1A, HSPH1 and the matrix metalloproteinase MMP-9 showed the most prominent increases whereas the mRNA concentrations of the YES1 oncogene (YES1), of CD160 (BY55), and of a member of the mitochondrial electron transport chain (ATP5s) were most strongly reduced. Remarkably, we could largely reproduce the data from a previous report by Connolly et al. (01) even though we used considerably different methodology. After acute exercise the genes with increased expression levels were highly significantly associated with the gene ontology terms heat-shock proteins, apoptosis and inflammation. The results demonstrate that gene expression changes in WBCs can reflect intensity and duration of exercise. Further analysis is needed to confirm the applicability of expression fingerprints as useful tools for monitoring exercise and training loads in order to avoid training associated health risks. Keywords: response to different loads of acute exercise

Project description:White blood cells (WBCs) express tens of thousands of genes. Their expression levels are modified by genetic and external factors. In further study we found that gene expression profiles of these cellls can serve as surrogate markers for monitoring exercise and training load.The purpose of the present study was to investigate the effects of acute exercise on gene expression profiles (GEPs) of PBMCs and T-lymphocytes in order to re-detect the patterns in subpopulations. The use of WBC subpopulations is necessary because of the well known subpopulation shifts that occur during physical activities. Three male probands performed an exhaustive treadmill test (ET) at 80% of their VO2max. PBMCs were isolated using BD Vacutainer CPT tubes containig Ficoll. T-lymphocytes were isolated from the PBMCs via rosetting technology. Gene expression profiles were measured using the Affymetrix GeneChipÂ® technology. After scaling, normalisation, and filtering groupwise and pairwise comparisons of gene expression intensities were performed. We found that sorting increases the detection sensitivity and enables the researcher to observe regulation that is hidden in heterogenous populations. We therefore suggest not to work on mixed nbut instead on sorted cells when performing gene expression analyses. Experiment Overall Design: Three healthy male probands executed an exhaustive treadmill test (80% VO2max) until individual exhaustion. Blood samples (16ml) were drawn before and one hour past the tests. PBMCs were isolated using the Ficoll density centrifugation methode. T-lymphocytes were isolated by adding rosetting anibodies zo the cells before centrifugation. Cells were lysed using Trizol and worked up with Qiagen RNeasy Micro columns. RNA was processed and hybridised on U133A 2.0 Affymetrix GeneChips. Samples were grouped and gene expression changes were detected via multiple algorithms included in GeneSpring 7.2 (Agilent). Experiment Overall Design: The four groups contained three samples related to the cell type "PBMC" or "T-cell" and "before exercise" or "1hour past exercise". TTest, GOs and KEGG classification, principal component analysis and hierarchical clstering were used to scan for gene expression profiles induced through the different exercise conditions.

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Passing the anaerobic threshold is associated with substantial changes in the gene expression profile in white blood cells

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