Computational protocol: Swimming-induced exercise promotes hypertrophy and vascularization of fast skeletal muscle fibres and activation of myogenic and angiogenic transcriptional programs in adult zebrafish

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Protocol publication

[…] Fast muscle samples for histochemical analyses were obtained from non-exercised and exercised zebrafish from Experiment 2. After placing the frozen samples in OCT embedding medium at -22°C, serial transverse sections of 16 μm in thickness were obtained in a cryostat (Leica CM3050S, Wetzlar, Germany) and mounted on 2% gelatinised slides. Two histochemical assays were performed on fast muscle serial sections: (1) succinate dehydrogenase (SDH) according to [] in order to demonstrate the aerobic or anaerobic characteristics of muscle fibres; and (2) endothelial ATPase according to [] to reveal muscle capillaries.All morphofunctional measurements of fast muscle cellularity and vascularization were performed on the sections processed for endothelial ATPase activity by using a light microscope (BX61, Olympus, Tokyo, Japan) connected to a digital camera (DP70, Olympus). Image Capturing software (DP Controller v. 1.1.1.65, 2002 Olympus) and Image Managing software (DP Manager v. 1.1.1.71, 2002 Olympus) were used to obtain digital microphotographs and to ensure accurate calibration of all measurements. All the parameters listed below were empirically determined from windows of tissue of approximately 5,5 × · 105 μm2 from two different zones or muscle fields in each sample using ImageJ analyzing software (v. 1.47, National Institutes of Health, USA). After testing for the absence of differences between the two muscle fields from each sample, the data obtained from both fields were considered together so that the sample size was large enough. The mean results presented throughout tables and figures were obtained from a sample of n = 8 fish for each condition (non-exercised and exercised).In order to determine if swimming-induced exercise caused changes in the morphometric and vascularization characteristics of fast muscle fibres, the following parameters were counted or calculated: capillary density (CD; capillary counts per unit cross-sectional area of muscle), fibre density (FD), capillary-to-fibre ratio (C/F = CD/FD; a parameter relatively independent of FCSA and a good indicator of muscle capillarization []), the number of capillaries in contact with each fibre (NCF) and the circularity shape factor (SF = 4 · π · FCSA/FPER2), which is an estimation of the circular morphology of the fibre (with a value of 1 for a perfect circle). Capillary and fibre counts were calculated and expressed as capillaries and fibres per mm2. The following fibre morphometric parameters were measured: fibre cross-sectional area (FCSA) and perimeter (FPER) and the maximal diffusion distance (MDD) between the capillary and the centre of the fibre. The total number of fibres analyzed in each muscle sample ranged from 200 to 250. The indices expressing the relationship between the number of capillaries per fibre and the fibre cross-sectional area (CCA = NCF · 103/FCSA) or fibre perimeter (CCP = NCF · 102/FPER) were also calculated. These indices are considered a measure of the number of capillaries per 1,000 μm2 of muscle FCSA and the number of capillaries per 100 μm of muscle FPER. Data for all the parameters are expressed as sample means ± standard error of the mean (SEM).The histograms of FCSA (Figure I-K) express the percentage frequencies of fibres grouped in intervals of 200 μm2 and error bars represent the SEM. To obtain the superposed curves in the histograms, a dynamic fitting by nonlinear regression was performed for each group of fish (non-exercised and exercised). The approximation was done by a log-normal (four parameters) equation with a dynamic fit option of 200 for both total number of fits and maximum number of iterations. The R values and parameters of the log-normal equations (a, b, x0 and y0), reported with their SEM, are shown in Additional file . [...] Single color microarray-based gene expression analysis was performed using an Agilent custom oligo microarray 4x44K with eArray design ID 021626 and containing a total of 43.863 probes of 60 oligonucleotides in length. Total RNA from fast skeletal muscle samples of individual adult zebrafish from Experiment 1 (non-exercised, n = 8; exercised, n = 8) was isolated with TRIzol (Invitrogen, Barcelona, Spain). RNA concentrations of the 16 samples used for microarray analyses, as measured with a NanoDrop ND-1000 (Thermo Scientific), ranged from 83 to 260 ng μl−1 (134 ± 15 ng μl−1), with average absorbance measures (A260/280) of 2.04 ± 0,03, and RNA Integrity Number (RIN) values of 8.85 ± 0.35, as obtained using a 2100 Bioanalyzer system (Agilent Technologies, Santa Clara, CA), that were indicative of clean and intact RNA suitable for microarray analysis. RNA was amplified and labeled with Cy3 dye using single color Low Input Quick Amp Labeling kit (Agilent Technologies) following the manufacturer’s indications using 200 ng of RNA in each reaction. Next, 1.65 μg of labeled cRNA were hybridized to the arrays. Overnight hybridization (17 h, 65°C and 10 rpm rotation) was performed in a Microarray Hybridization Oven (Agilent Technologies). After hybridization, microarrays were washed with Gene Expression Wash Buffers 1 and 2 (Agilent Technologies) and scanned using the High-Resolution C Scanner (Agilent Technologies). Feature Extraction Software 10.7.3 (Agilent Technologies) was used for spot to grid alignment, feature extraction and quantification. Processed data were subsequently imported into GeneSpring GX 11.5 (Agilent Technologies). Significance cut-offs for the ratios of exercised vs non-exercised were set at at P < 0.01 (sample t-test) and >1-fold change for differentially expressed genes (DEGs). For the DEGs, gene IDs were converted to human ENSEMBL gene IDs using g:orth function from G:profiler (http://biit.cs.ut.ee/gprofiler), taking advantage of the more complete gene ontology (GO) annotations of the human genes and improving, in this way, the subsequent analysis of the functional categories. The complete microarray data have been deposited in NCBI´s Gene Expression Omnibus and are accessible through GEO Series accession number GSE58929 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE58929). GO enrichment analysis was performed using Database for Annotation, Visualization and Integrated Discovery (DAVID) software tools (http://david.abcc.ncifcrf.gov), and the resulting categories were considered significant at P < 0.05. Pathway and network analyses were conducted using Ingenuity® Systems Pathway Analysis (IPA) software (Redwood City, CA). To analyze by IPA, annotated spots were mapped to zebrafish and human orthologs using BLASTN against the Ensembl Danio rerio gene database (v.Zv9.66) and the Homo sapiens transcript database (v.GRCh37.66) with an e-value ≤1.00E − 05. Human and zebrafish orthologs were then compared to the Ingenuity® Knowledge Base (http://www.ingenuity.com) and significantly altered pathways and biological functions were determined using the Fisher exact test (P < 0.05). [...] For capillarization and fibre morphometrical parameters, the normality of the data was tested by the Kolmogorov-Smirnov test (with Lilliefors’ correction) and the comparisons between the two groups of fish (non-exercised and exercised) were analysed by Student’s t tests. To test the differences between non-exercised and exercised fish in the frequencies for three intervals of FCSA measured (i.e. fibres with areas below 1.200 μm2, between 1.200 and 2.400 μm2 and above 2.400 μm2; Additional file : Table S1), Student’s t tests were performed. The normalizing arcsine transformation was applied as a previous step. All statistical analyses were performed using SigmaStat 4.0 (in SigmaPlot 11.0 Software, Systat Software Inc., San Jose, CA, USA). […]

Pipeline specifications

Software tools ImageJ, GeneSpring GX, g:Profiler, DAVID, BLASTN, SigmaPlot
Applications Miscellaneous, Microscopic phenotype analysis
Organisms Danio rerio