BioProject

Twenty healthy subjects (25±5yrs) completed two high-intensity interval training interventions (training and retraining) lasting 8 weeks separated by 12 weeks of detraining. More...

Twenty healthy subjects (25±5yrs) completed two high-intensity interval training interventions (training and retraining) lasting 8 weeks separated by 12 weeks of detraining. Measurements at baseline and after training, detraining and retraining included maximal oxygen consumption (V̇O2max), along with vastus lateralis biopsy for genome wide DNA methylation using Illumina Epic arrays in 5 of the participants for all conditions (baseline, training, detraining and retraining). Overall design: MATERIALS AND METHODS Subjects The study intervention was conducted at the University of Pavia, Italy. Twenty male (n = 11) and female (n = 9) adults were recruited from the local community. Inclusion criteria included: To have not been involved in structured training programs before; maximal oxygen consumption (V ̇O2max), determined by an initial screening test, lower than 40 and 45 ml·min−1·kg−1 for women and men, respectively. Exclusion criteria specified that all participants were free from major diseases at the pulmonary, cardiovascular and muscle level and they were not taking any drugs. All procedures were in accordance with the Declaration of Helsinki and the study was approved by the local ethics committee (Besta 64-19/07/2019) and participants gave their written informed consent after being informed about objectives, methods and risks of the study. Below are the participants anthropometrics and physiological characteristics measured during the initial screening test grouped according to sex. V ̇O2max, maximal oxygen uptake. All values are means ± SD. Males (n = 11), Age (yrs) 27 ± 5, Weight (kg) 72.1 ± 10.7, Height (cm)177 ± 5, V ̇O2max (ml·min−1·kg−1) 36.8 ± 8.3, V ̇O2max (l·min−1) 2.601 ± 0.448 Females (n = 9), Age (yrs) 23 ± 3, Weight (kg) 58.7 ± 7.2, Height (cm)167 ± 4, V ̇O2max (ml·min−1·kg−1), 34.1 ± 5.3, V ̇O2max (l·min−1) 1.985 ± 0.308 Study design The current study exposed the same individuals to two identical 8-week high-intensity interval training periods separated by a three-month washout period during which participants were instructed to return to their habitual life. Levels of physical activity were monitored before and throughout the entire period of the study by accelerometers (wGT3X-BT, ActiGraph, Florida, USA). Data collection was performed at four different time points: at baseline (BASELINE), after the first training period (TRAINING), following detraining (DETRAINING) and after retraining (RETRAINING). For each time point participants visited the laboratory on two separate occasions. During the first visit, anthropometric measurements were collected, and an incremental cycle ergometer exercise test up to voluntary exhaustion was performed. On the second visit, approximately 100 mg of skeletal muscle tissue was obtained from the vastus lateralis muscle under local anesthesia (1% lidocaine) for genome wide DNA methylation (methylome), targeted gene expression based on genes that demonstrated significantly differentially methylation positions (DMPs) or regions (DMRs) (described below) and protein abundance based on molecular pathways demonstrating retained epigenetic and or transcriptional retention. Participants were instructed to abstain from strenuous physical activity for at least 48 h prior to each testing session. Training Exercise prescription consisted of two identical 8-week periods of high-intensity interval training (HIIT) based on individual results obtained from the exercise incremental tests. The first three training sessions were conducted under the supervision of a researcher, who oversaw giving adequate instructions about the training procedures. The remaining training sessions (3/week) were conducted at home on electronically braked cycle ergometer. Time, heart rate (HR) and power (W) from each session were recorded and uploaded on a web-based app (MyZone, England, UK) to allow the researchers to check the adherence to the training regimen. Every week the subjects were contacted by phone to monitor progression, provide feedback and encouragement, and to answer any questions. Exercise sessions were composed by 10 min of warm-up followed by high-intensity bouts of either short (1-2 min) or long (3-4 min) duration. Exercise prescription varied during the training period to facilitate participant motivation and compliance, as detailed previously (Robach et al., 2014). To avoid stagnation (Granata et al., 2016a) the training stimulus (power and repetitions) was progressively incremented. An identical training protocol was applied for both training and retraining. Incremental exercise Incremental exercise was performed on an electronically braked cycle ergometer (818E, Monark, Sweden) to determine maximal oxygen consumption (V ̇O2max), gas exchange threshold (GET), and respiratory compensation point (RCP). Pedaling frequency was digitally displayed to the subjects, and subjects were asked to keep a constant cadence throughout the tests between 70 and 80 rpm. Power was increased 10-15 W every minute, depending on the individual’s fitness aiming to allow the subjects to reach voluntary exhaustion in 10–15 min. Voluntary exhaustion was defined as the incapacity to maintain pedaling frequency for 5 s at the imposed work rate despite vigorous encouragement by the researchers. After 30 min of recovery, all participants performed a verification trial consisting of a constant work rate exercise at 90% of the highest power attained in the incremental test (Wmax) (Rossiter et al, 2006). Pulmonary ventilation (VE, in BTPS [body temperature (37°C), ambient pressure and gas saturated with water vapor]), oxygen consumption (V ̇O2), and CO2 output (V ̇CO2), both in STPD (standard temperature [0°C or 273 K] and pressure [760 mmHg] and dry [no water vapor]), were determined breath-by-breath by a metabolic cart (Vyntus CPX, Vyaire Medical GmbH, Germany). Before each test, gas analyzers were calibrated with ambient air and a gas mixture of known concentration (O2: 16%, CO2: 4%) and the turbine flowmeter was calibrated with a 3-L syringe at three different flow rates. RER was calculated as V ̇CO2/V ̇O2. HR was recorded by using a HR chest band (HRM-Dual, Garmin, Kansas, USA). Rating of perceived exertion (RPE) was determined using Borg® 6–20 scale every 2 min through the test (Borg, 1982). At rest, and at 1, 3, and 5 min of recovery, 20 μL of capillary blood was obtained from a preheated earlobe for blood lactate concentration (Biosen C-line, EKF, Germany); the analyzer was frequently calibrated with a standard solution containing 12 mmol·L−1 of lactate. The highest 20-s averaged cardiopulmonary and metabolic data recorded during the whole incremental test (i.e. including the verification phase) were taken as maximal values (Martin-Rincon et al. 2019). GET was determined by two independent investigators by using the modified “V-slope” method (Beaver et al., 1986) and “secondary criteria”. RCP was determined as the point where end-tidal PCO2 began to fall after a period of isocapnic buffering (Whipp et al, 1989). This point was confirmed by examining V ̇E/V ̇CO2 plotted against V ̇O2 and by identifying the sec breakpoint in the V ̇E-to-V ̇O2 relation. Muscle Biopsy Fifteen participants out of 20 [male (n = 9) and female (n = 6)] agreed to undergo muscle biopsy for all the time points required by the experimental protocol. Resting muscle biopsies were taken from the vastus lateralis muscle using a 130 mm (6”) Weil-Blakesley rongeur (NDB-2, Fehling Instruments, GmbH&Co, Germany) under local anesthesia (1% lidocaine). After collection, muscle samples were cleaned of excess blood, fat, and connective tissue in ice-cold BioPS, a biopsy-preserving solution containing (in mM) 2.77 CaK2EGTA, 7.23 K2EGTA, 5.77 Na2ATP, 6.56 MgCl2, 20 taurine, 50 MES (2-(N-morpholino) ethanesulfonic acid), 15 Na2phosphocreatine, 20 imidazole, and 0.5 dithiothreitol adjusted to pH 7.1 (Doerrier et al., 2018). A portion of ~20 mg of muscle tissue was immediately submerged in Allprotect Tissue Reagent (Qiagen, Netherlands) following the manufacturer’s instructions to stabilize and protect cellular DNA and was stored at -20°C for subsequent DNA methylome analysis (described below). A specimen of ~20-30 mg was rapidly frozen by immersion in liquid nitrogen and stored at -80°C for RNA isolation and gene expression analysis (described below). Finally, a portion of ~20-30 mg from each muscle sample was rapidly frozen by immersion in liquid nitrogen and stored at -80°C for protein analysis. Fifteen out of 15 subjects were analyzed for RNA/gene expression, 9 subjects were analyzed for protein abundance and 5 subjects per time point (BASELINE, TRAINING, DETRAINING, RETRAINING) for DNA methylome analysis. Methylation analysis After power analysis conducted to detect a greater than 1.05 (5%) fold change in methylation based on our previous studies (Seaborne et al., 2018a), a sample size of 4 in a within-subject design was determined as sufficient to detect statistically significant changes in methylation over the baseline, training, detraining and retraining time points. Thereby, five (n = 5) subjects were analyzed in the present data set for DNA methylome analysis. Tissue Homogenization, DNA Isolation, and Bisulfite Conversion. Tissue samples were homogenized for 45 s at 6,000 rpm × 3 (5 min on ice in between intervals) in lysis buffer (180 μl buffer ATL with 20 μl proteinase K) provided in the DNeasy spin column kit (Qiagen, United Kingdom) using a Roche Magnalyser instrument and homogenization tubes containing ceramic beads (Roche, United Kingdom). The DNA was then bisulfite converted using the EZ DNA Methylation Kit (Zymo Research, CA, United States) as per manufacturer’s instructions. Infinium Methylation EPIC Beadchip array. All DNA methylation experiments were performed in accordance with Illumina manufacturer instructions for the Infinium Methylation EPIC 850K BeadChip Array (Illumina, USA). Methods for the amplification, fragmentation, precipitation and resuspension of amplified DNA, hybridization to EPIC BeadChip, extension and staining of the bisulfite converted DNA was conducted as detailed in paper from Seaborne and colleagues (Seaborne et al., 2018). EPIC BeadChips were imaged using the Illumina iScan System (Illumina, United States). DNA methylation analysis, CpG enrichment analysis (GO and KEGG pathways), differentially methylated region (DMR) analysis and Self Organizing Map (SOM) temporal profiling. Following DNA methylation quantification via Methylation EPIC BeadChip array, raw.IDAT files were processed using Partek Genomics Suite V.7 (Partek Inc. Missouri, USA) and annotated using the MethylationEPIC_v-1-0_B4 manifest file. We first checked the average detection p-values for each sample across all probes. The mean detection p-value for all samples across all probes was 0.000295, and the highest for any given sample was 0.000597, which is well below the recommended 0.01 in the Oshlack workflow (Maksimovic et al., 2017). We also produced density plots of the raw intensities/signals of the probes per sample. These demonstrated that all methylated and unmethylated signals were over 11.5 (mean median signal for methylated probes was 11.56 and unmethylated probes 11.69), and the mean difference between the median methylation and median unmethylated signal was 0.13, well below the recommended difference of less than 0.5 (Maksimovic et al., 2017). Upon import of the data into Partek Genomics Suite we removed probes that spanned X and Y chromosomes from the analysis due to having both males and females in the study design, and although the average detection p-value for each sample was very low (no higher than 0.000597) we also excluded any individual probes with a detection p-value that was above 0.01 as recommended (Maksimovic et al., 2017). Out of a total of 865,859 probes removing those on the X & Y chromosome (19,627 probes) and with a detection p-value above 0.01 (4,264 probes) reduced the total probe number to 843,355 (note some X&Y probes also had detection p-values of above 0.01). We also filtered out probes associated with single-nucleotide polymorphisms (SNPs) and any known cross-reactive probes using previously defined SNP and cross-reactive probe lists from EPIC BeadChip 850K validation studies (Pidsley et al., 2016). This resulted in a final list of 791,084 probes to be analysed. Following this, background normalization was performed via functional normalization (with noob background correction) as previously described (Maksimovic et al., 2012). Following functional normalization, we also undertook quality control procedures via Principle Component Analysis (PCA), density plots by lines as well as box and whisker plots of the normalized data for all samples. Any outlier samples were detected using Principle Component Analysis (PCA) and the normal distribution of β-values. Outliers were detected if they fell outside 2 standard deviations (SDs) of the ellipsoids and/or if they demonstrated different distribution patterns to the samples of the same condition. We confirmed that no samples demonstrated large variation [variation defined as any sample above 2 standard deviations (SDs) – depicted by ellipsoids in the PCA plots and/or demonstrating any differential distribution to other samples, depicted in the signal frequency by lines plots. Therefore, no outliers were detected in this sample set. Following normalization and quality control procedures, we undertook differentially methylated position (DMP) analysis by converting β-values to M-values [M-value = log2(β/(1 − ββ)], as M-values show distributions that are more statistically valid for the differential analysis of methylation levels (Du et al, 2010). We undertook a one-way ANOVA for comparisons of baseline, training, detraining and retraining muscle tissue. Any differentially methylated CpG position (DMP) with an unadjusted p-value of ≤ 0.01 was used as the statistical cut off for the discovery of DMPs. We then undertook CpG enrichment analysis on these differentially methylated CpG lists within gene ontology (GO) and KEGG pathways (Kanehisa & Goto, 2000; Kanehisa et al., 2016, 2017) using Partek Genomics Suite and Partek Pathway. Differentially methylated region (DMR) analysis, that identifies where several CpGs are consistently differentially methylated within a short chromosomal location/region, was undertaken using the Bioconductor package DMRcate (DOI: 10.18129/B9.bioc.DMRcate). Finally, to plot and visualize temporal changes in methylation across the timepoints we implemented Self Organizing Map (SOM) profiling of the change in m-value within each condition using Partek Genomics Suite. Less...