ABSTRACT
Muscle fibres are classified as fast, intermediate and slow. In vitro myoblast cell culture model from fast muscle is a very useful tool to study muscle growth and development; however, similar models for slow muscle do not exist. Owing to the compartmentalization of fish muscle fibres, we have developed a slow myoblast cell culture for rainbow trout (Oncorhynchus mykiss). Slow and fast muscle-derived myoblasts have similar morphology, but with differential expression of slow muscle markers such as slow myhc, sox6 and pgc-1α. We also characterized the mir-133 and mir-499 microRNA families in trout slow and fast myoblasts as a case study during myogenesis and in response to electrostimulation. Three mir-133 (a-1a, a-1b and a-2) and four mir-499 (aa, ab, ba and bb) paralogues were identified for rainbow trout and named base on their phylogenetic relationship to zebrafish and Atlantic salmon orthologues. Omy-mir-499ab and omy-mir-499bb had 0.6 and 0.5-fold higher expression in slow myoblasts compared with fast myoblasts, whereas mir-133 duplicates had similar levels in both phenotypes and little variation during development. Slow myoblasts also showed increased expression for omy-mir-499b paralogues in response to chronic electrostimulation (7-fold increase for omy-mir-499ba and 2.5-fold increase for omy-mir-499bb). The higher expression of mir-499 paralogues in slow myoblasts suggests a role in phenotype determination, while the lack of significant differences of mir-133 copies during culture development might indicate a different role in fish compared with mammals. We have also found signs of sub-functionalization of mir-499 paralogues after electrostimulation, with omy-mir-499b copies more responsive to electrical signals.
INTRODUCTION
Skeletal muscle is the most abundant tissue in teleost fish and can represent up to 60% of total body mass (Johnston, 2001). Skeletal muscle is key for fish propulsion, represents the biggest protein reservoir and is the main product of the aquaculture industry (Johnston, 2001; Sänger and Stoiber, 2001).
Muscle fibre types are classified based on their contractile and metabolic properties as fast, intermediate and slow (Johnston et al., 2004). Fast fibres comprise up to 80–90% of the skeletal muscle and are characterized by fast-twitch, predominantly anaerobic metabolism, low concentrations of myoglobin, mitochondria content and lipids, and low capillary density. The fast fibres are recruited during intense activity, associated with food capture and escape behaviour (Sänger and Stoiber, 2001). Slow fibres comprise 5–20% of muscle mass and are located along the fish body, with a thicker region on the lateral line. They are characterized by having slow-twitch, predominantly aerobic metabolism, high levels of myoglobin, mitochondria content and lipids, and high capillary density (Sänger and Stoiber, 2001). Despite its relatively low abundance, the slow muscle is the main tissue involved in sustained swimming and is critical for middle and long-distance migrations (Bone, 1978; Sänger and Stoiber, 2001). The intermediate fibres have intermediate contractile and metabolic properties between fast and slow fibres and are physically located between these two compartments, representing a very marginal proportion of the total skeletal muscle (Sänger and Stoiber, 2001).
Postembryonic skeletal muscle growth occurs through the activation of myogenic precursor cells (MPCs). MPCs are located between the basal lamina and the sarcolemma of the muscle fibres, and under the absence of stimuli they remain in a quiescent state (then known as satellite cells) (Hollway et al., 2007; Rossi and Messina, 2014; Seger et al., 2011). Satellite cells re-enter the cell cycle in response to different stimuli, such as growth factors, hormones, cytokines, injury, exercise and nutrition, becoming proliferative myoblasts that can either fuse to each other, forming new fibres (hyperplasia), or fuse to pre-existent fibres, contributing to their growth in size (hypertrophy) (Johnston, 2006; Johnston et al., 2011), a process globally known as myogenesis. The establishment of the fish fast myoblast cell culture model has helped to characterize the molecular networks controlling myogenesis (Bower and Johnston, 2010b; Garcia de la serrana and Johnston, 2013; Johnston et al., 2011). The in vitro model recapitulates the main stages of the myogenesis, starting with round quiescent cells, followed by proliferative myoblasts and differentiating myotubes (Gabillard et al., 2010; Vélez et al., 2016). Myoblast cell culture facilitates the study of the molecular networks involved in muscle formation in response to specific inputs, such as growth factors and nutrition (Duran et al., 2015, 2019; Garcia de la serrana and Johnston, 2013; Johnston et al., 2011; Vélez et al., 2014). The compartmentalization of skeletal muscle in fish makes it possible to isolate myoblasts from fast and slow muscle, something very difficult in mammals owing to the mixture of fast and slow fibres (Schiaffino and Reggiani, 2011). Until now, the myoblast cell culture had only been developed for fast skeletal muscle, and a similar model for slow muscle was not established.
The teleost lineage underwent a specific whole genome duplication (WGD) around 450–320 million years ago (Mya) (Jaillon et al., 2004). As a result, several signalling pathways and molecular networks had some of their components expanded with multiple paralogue copies. It has been estimated that approximately 15–21% of the duplicated paralogues originated during the WGD have been retained (Garcia de la serrana et al., 2014b). In addition, the salmonid lineage went through an additional WGD around 75 Mya with an estimated 50% paralogue retention (Macqueen and Johnston, 2014; Macqueen et al., 2010, 2013). Paralogue genes can be retained after a WGD through three main mechanisms: sub-functionalization (each paralogue retains part of the original function of the ancestral gene), neo-functionalization (paralogue acquires a different function from the ancestral gene) or redundancy (multiples copies of a gene confer some advantage) (Bower and Johnston, 2010a; Garcia de la serrana and Johnston, 2013; Garcia de la serrana et al., 2014b, 2017; Maere and Van de Peer, 2010).
There is also evidence of microRNA (miRNA) families expanded after the teleost WGD (Berthelot et al., 2014). The primary function of these types of small noncoding RNAs (ncRNA) is the post-transcriptional regulation of gene expression, promoted by translational inhibition and decay of target messenger RNAs (mRNAs) (Ge and Chen, 2011). miRNAs play an orchestrated role in the regulation of multiple targets, controlling several signalling pathways and biological functions (Goljanek-Whysall et al., 2012; van Rooij et al., 2008). Based on the high conservation observed in miRNAs among vertebrates, it can be anticipated that a considerable set of mRNAs are under the modulation by miRNAs in teleosts (Bizuayehu and Babiak, 2014). Some miRNAs such as mir-1, mir-133, mir-206 and mir-499 are specifically or highly expressed in cardiac and/or skeletal muscles, and are involved in myogenesis, myoblast proliferation, differentiation, fibre type specification and muscle regeneration (Chen et al., 2006; Ge and Chen, 2011; van Rooij et al., 2009). Previous studies in pacu (Piaractus mesopotamicus) showed that fast and slow muscles have different miRNA expression patterns, as was the case of miR-499, which exhibited higher levels of transcription in slow muscle (Duran et al., 2015), suggesting its involvement in the specification and maintenance of slow-twitch phenotype as previously observed in mammals (McCarthy, 2011; van Rooij et al., 2009). In such a context, the innervation pattern has been suggested to be essential for muscle fibre type specification; a tonic and low-frequency neural stimulation induces the slow phenotype, whereas a phasic and high-frequency neural stimulation promotes the fast phenotype (Chin et al., 1998; Olson and Williams, 2000). In the past years, studies have shown that muscle fibre neural activation can be recreated by electrical pulse stimulation (EPS) of cultured skeletal muscle cells (Fujita et al., 2007; Marotta et al., 2004; Thelen et al., 1997). EPS models are useful to investigate adaptive responses of skeletal muscle cells to different patterns of contractile activity, for instance the study of molecular and cellular mechanisms during simulation of resistance or endurance training (Burch et al., 2010; Nedachi et al., 2008; Nikolić et al., 2012; Silveira et al., 2006). Therefore, the electrostimulation represents an important tool with which to investigate the roles of molecules involved with the regulation of muscle growth and phenotype, such as the miRNAs.
In the present work, we established a slow muscle myoblast cell culture from rainbow trout (Oncorhynchus mykiss) (Cleveland and Weber, 2010; Gabillard et al., 2010; Montserrat et al., 2007a; Seiliez et al., 2008) and used it to characterize the mir-133 and mir-499 families during slow and fast myoblast development and in response to EPS applied on slow muscle cell cultures.
MATERIALS AND METHODS
Ethics statement and animals
All experiments and procedures were approved by the Animal Welfare and Ethics Committee (AWEC) of the University of St Andrews and were carried out in accordance with relevant guidelines and regulations. Rainbow trout [Oncorhynchus mykiss (Walbaum 1792)] juveniles (10–15 g) were obtained from Frandy Farm (Gleneagles, Scotland) and transported to the Scottish Oceans Institute aquarium facilities (University of St Andrews). Animals were evenly distributed in duplicated 200 litre fibreglass tanks, maintained in a freshwater re-circulatory system at a temperature between 12 and 15°C and fed ad libitum daily with commercial diet provided by the same farm of origin. Trout were humanely killed by head dislocation followed by the destruction of the brain with a scalpel according to Schedule 1 protocols as described in the Animals (Scientific Procedures) Act 1986 (Home Office Code of Practice. HMSO: London, January 1997).
Myoblast cell culture
A total of four independent myoblast cell cultures were performed as previously described (Fauconneau and Paboeuf, 2000). Briefly, fast muscle samples were collected from the epaxial region and slow muscle was carefully dissected around the lateral line (n=14–16 fish per culture until reaching a total of 20 g per tissue). Fast and slow muscles were mechanically dissociated with scalpels and enzymatically digested with 0.2% type I collagenase (Sigma-Aldrich) and 0.1% trypsin (Sigma-Aldrich). Cells were filtered through 40 and 100 µm cell strainers (Thermo Fisher Scientific) to remove any debris. After several washes, cells were resuspended in Dulbecco's modified Eagle's medium (DMEM, 9 mmol l−1 NaHCO3, 20 mmol l−1 Hepes, pH 7.4; Sigma-Aldrich) with 10% fetal bovine serum (FBS) and 1% antibiotic mixture (Sigma-Aldrich). After cell counting in a Neubauer chamber, cells were diluted to a final concentration of 2×106 cells ml−1 and seeded in poly-l-lysine and laminin pre-treated 6-well plates. Slow and fast myoblasts were maintained at 18°C for a total period of 12 days. Culture media were changed daily, and myoblast morphology was regularly monitored using a Leica DM IL Inverted Microscope coupled with the Leica DFC320 Digital Camera system. Total RNA was extracted from cells at days 2, 4, 6, 8, 10 and/or 12.
Electrical pulse stimulation (EPS)
Electrostimulation was performed using a C-Pace EP Cell Culture Stimulator in conjunction with the C-Dish Electrode Assemblies (IonOptix). Myoblasts were electro-stimulated daily from day 4 of culture until day 10 following three different protocols: control plate (CTR; non-treated cells), acute treatment (A-EPS; cells treated with acute and high-frequency stimulation, simulating fast muscle innervation) and chronic treatment (C-EPS; cells treated with chronic and low-frequency stimulation, simulating slow muscle innervation). The acute treatment was applied for 15 min and the myoblasts were submitted to pulse trains of 10 Hz and 30 V for 10 ms, given every fifth second. The chronic treatment was applied for 2 h and the myoblasts were submitted to pulse trains of 1 Hz and 30 V for 2 ms. The myoblasts were electro-stimulated in serum-free DMEM and remained resting for 10 min before adding fresh medium. RNA extractions for days 6, 8 and 10 of cell culture were performed 2 h after the EPS.
miRNA phylogenetic analysis
Initially, the precursor sequences of miRNAs mir-133, mir-499 and mir-206 (an miRNA also highly expressed in muscle; Ge and Chen, 2011; Ma et al., 2015) were obtained from the zebrafish (Danio rerio) genome using the Ensembl Genome Browser 89 (http://www.ensembl.org/index.html). Zebrafish miRNAs were used as query against the available rainbow trout genome in Genoscope (https://www.genoscope.cns.fr/trout/) (Berthelot et al., 2014). Identified trout orthologues were initially named as omy-mir-133 and omy-mir-499 until their identity was phylogenetically established. Orthologues for mir-133 and mir-499 precursor sequences (pre-miRNA) from different teleosts (Astyanax mexicanus, D. rerio, Gasterosteus aculeatus, Oreochromis niloticus, Oryzias latipes, Takifugu rubripes, Tetraodon nigroviridis) and mammals (Homo sapiens, Mus musculus, Pan troglodytes and Rattus norvegicus) were retrieved from the Ensembl database. In addition, pre-miRNA orthologues for Atlantic salmon (Salmo salar) and coho salmon (Oncorhynchus kisutch) were also obtained from SalmoBase (https://salmobase.org/) (Samy et al., 2017) and NCBI (http://www.ncbi.nlm.nih.gov). The pre-miRNA sequences (Table S1) were aligned using MAFFT version 7 (http://mafft.cbrc.jp/alignment/server/), while MEGA7 software (Kumar et al., 2016) was used to estimate the best evolutionary model from aligned sequences. Bayesian MCMC (Markov chain Monte Carlo) phylogenetic trees following a Yule speciation process model and UPGMA (unweighted pair group method with arithmetic mean) starting tree were generated for each alignment using BEAST v1.7.4 software (Drummond et al., 2012) with 10,000,000 seeds. Final Bayesian trees were generated using TreeAnnotator v.1.7 with a burn-in value of 1000. All trees were visualized and edited using FigTree v.1.4.2 (http://tree.bio.ed.ac.uk/software/figtree/).
RNA extraction and reverse transcription
Total RNA was extracted using TRIsure™ (Bioline Reagents), according to the manufacturer's recommendations, and stored at −80°C for further analysis. Total RNA was quantified by spectrophotometry using a Nanodrop (ND1000) (Thermo Fisher Scientific) while integrity was evaluated by 1% ethidium bromide agarose gel electrophoresis. All samples had 280/260 nm and 230/260 nm ratios above 1.8, indicating high-quality RNA. A total of 224 ng of total RNA per sample was reverse transcribed using the miScript II RT Kit and the QuantiTec Reverse Transcription Kit (Qiagen, Germany), following the manufacturer's guidelines. The resulting cDNA was used for quantitative real-time PCR (qPCR).
Primer design
Primers for rainbow trout slow myosin heavy chain (smyhc), fast myosin heavy chain (fmyhc), sry sex determining region Y-box 6 (sox6), six homeobox 1 (six1), insulin-responsive glucose transporter type 4 (glut4), late endosomal/lysosomal adaptor, mapk and mtor activator 3 (lamtor3), ras related GTP binding D (ragd), regulatory associated protein of mtor complex 1 (rptor), muscle atrophy f-box protein (mafbx/fbxo32), peroxisome proliferator-activated receptor gamma coactivator 1 alpha (pgc-1α), creatine kinase, m-type a (ckma), creatine kinase, m-type b (ckmb), myogenin (myog), ribosomal protein L13 (rpl13) and ribosomal protein L19 (rpl19), and paralogues of omy-mir-133 (133a-1a, 133a-1b and 133a-2), omy-mir-499 (499aa, 499ab, 499ba, 499bb), omy-mir-206-1 and U6 snRNA (U6 small nuclear RNA) were designed using Primer3 v.0.4.0 (Koressaar and Remm, 2007; Untergasser et al., 2012) (Table S2). The precursor sequences from each rainbow trout miRNA were used to design the forward and reverse primers in regions with low similarity in order to amplify individual paralogues (primers for omy-mir-499aa amplified both 499aa and 499ab copies, resulting in a global omy-mir-499a expression (aa+ab). Primers for miRNA were designed to work at 60°C and amplify 60–100 bp regions while primers for mRNA were designed to work at 60°C and amplify 50–200 bp regions. Any possible hairpin, self-dimer or cross-dimer structures formed by the primer pairs were estimated using NetPrimer software (Premier Biosoft).
Quantitative real-time PCR (qPCR)
All qPCR performed was compliant with the Minimum Information for Publication of Quantitative Real Time PCR experiments (MIQE) guidelines (Bustin et al., 2009). Each qPCR reaction contained 6 µl of diluted cDNA (1:40), 7.5 µl of SensiFAST™ SYBR® master mix (Bioline Reagents) and 1.5 µl of 500 nmol l−1 forward/reverse primer mix. The reactions were performed in duplicate under the following conditions: one cycle at 95°C for 2 min followed by 40 cycles of denaturation at 95°C for 5 s and annealing/extension at 65°C for 20 s in an MX3005P Real Time PCR System (Agilent Technologies). The specificity of each primer set was confirmed by the presence of a single-peak dissociation curve. Gene expression was estimated using the 2–ΔΔC_{\rm t} method (Livak and Schmittgen, 2001). Different housekeeping genes were tested (rpl13, rpl19, omy-mir-206-1 and U6 snRNA) and NormFinder software (Andersen et al., 2004) was used to identify the optimal normalization gene for miRNA and mRNA expression. Rpl13 and omy-mir-206-1 were identified as the most suitable housekeeping genes for mRNA and miRNA expression, respectively. The secondary structure of the identified miRNA precursor sequences was predicted using the RNAfold WebServer (Gruber et al., 2008) (Fig. S1).
Statistical analysis
Statistical analyses were performed using RStudio v1.0.136 (https://rstudio.com/) and statistical significance was set at 5% (P<0.05). The normality of the expression data was tested using the Shapiro–Wilk test. When the normality assumption was fulfilled, data were analyzed using a two-way ANOVA followed by a post hoc Tukey's honestly significant difference (HSD) test, with the tissue of origin (tissue) and the day of development (development) as factors. When the normality assumption was not fulfilled, data were transformed using the Box–Cox power transformation approach (Box and Cox, 1964) and analyzed as described. In addition, miRNA expression data from slow and fast myoblast comparison were analyzed using the unpaired t-test with tissue as a factor, and miRNA expression data from EPS treatments were analyzed using a one-way ANOVA followed by a post hoc Dunn's test, with treatment as a factor for the analysis. Pearson's correlation was used to access interesting relationships between evaluated genes. All graphs were constructed using the ggplot2 R package (Wickham, 2016).
RESULTS
Myoblast cell culture
Fast myoblast cell culture requires small juveniles (3–5 g) in order to maximize the number of myoblasts obtained (Castillo et al., 2002, 2006; Garcia de la serrana and Johnston, 2013; Montserrat et al., 2007b). However, slow muscle extraction requires larger animals in order to be able to discriminate between tissues and to dissect pure slow muscle. We found that rainbow trout around 15 g of body mass yield enough fast and slow myoblasts from individual animals to perform the experiment described in the present study (Fig. 1A). Compared with fast skeletal muscle, slow muscle extraction requires a harder mechanical dissociation, does not change DMEM colour (lactate from fast muscle turns it orange) and originates a top layer of fat that, if not removed, would reduce the efficiency of extraction (Fig. 1B, black arrow). At the end of the extraction protocol, slow skeletal muscle consistently yielded more cells per gram of tissue than fast skeletal muscle (data not shown). Slow and fast myoblasts were morphologically very similar with equivalent developmental stages during the culture progression: round mononucleated cells between days 1 and 2, proliferative myoblasts between days 3 and 7 and distinctive myotubes between days 8 and 12 (Fig. 1C, white arrows).
Characterization of slow muscle-derived myoblast cell culture
Myogenic nature of the cell cultures was confirmed by the expression of the muscle-specific transcription factor myogenin (myog) during the myotube formation phase (Fig. S2) (Johnston, 2006). The phenotype of slow-derived myoblasts was confirmed by analyzing the expression of smyhc, fmyhc, six1 and sox6 during the culture progression (Fig. 2). Expression of fmyhc and smhyc was significantly different between cell cultures (tissue P<0.001 and development P<0.001) (Fig. 2A,B). The abundance of fmyhc was 2.5-fold higher in fast muscle cell culture between days 8 and 12 (Fig. 2B), while smyhc showed a >12-fold increase in slow muscle myotubes (Fig. 2A). The expression levels of the six1 and sox6 transcription factors were higher in fast than slow myoblast cell culture (tissue P<0.001 for both genes) (Fig. 2C,D). Both transcription factors had maximal abundance between days 6 to 10 (development P<0.001 for both genes) (Fig. 2C,D).
In order to investigate metabolic differences between tissues, we studied the expression of genes related to protein balance (lamtor3, ragd, rptor and mafbx), glucose uptake (glut4) and energy (pgc1α, ckma and ckmb) (Fig. 3). Despite the differences between slow and fast muscle cells not being significant for glut4, lamtor3 and ragd (tissue P=0.58, 0.22 and 0.63, respectively) (Fig. 3A–C), their transcription was slightly higher in slow cell culture and decreased between days 8 to 12 (Fig. 3A,C). In both tissues, the mafbx expression similarly (tissue P=0.05) decreased suddenly after day 2 (development P<0.001) and remained low until the end of the culture, while rptor did not change between tissues (tissue P=0.53) or culture development (development P=0.07) (Fig. 3D,E). In contrast, pgc1α expression was stable during the cell culture (development P=0.59) and significantly higher in slow culture (tissue P<0.001) (Fig. 3F). The expression pattern of ckma and ckmb paralogues was very similar between slow and fast muscle cells (tissue P=0.28 for ckma and P=0.36 for ckmb), with maximal expression during myotube formation (days 8 to 12) (development P<0.001 for both genes) (Fig. 3G,H).
miRNA identification
Several members of the mir-133 and mir-499 families were identified for rainbow trout, coho salmon and Atlantic salmon. We used phylogenetic analysis to establish their identity and name them based on the existent zebrafish and salmonid nomenclature. Phylogenetic analysis confirmed the existence of three copies of mir-133 (Fig. 4) and four of mir-499 (Fig. 5) in rainbow trout. According to the tree topology, rainbow trout paralogues were named as omy-mir-133a-1a, omy-mir-133a-1b, omy-mir-133a-2, omy-mir-499aa, omy-mir-499ab, omy-mir-499ba and omy-mir-499bb (Figs 4 and 5; Table S1). Globally, miRNA sequences were highly conserved, with identities over 92% (Table S3). We also observed that paralogues of the same family had very similar secondary structures while differences between mir-133 and mir-499 families were also clear (Fig. S1). Owing to the high degree of identity, the primers designed for omy-mir-499aa also amplified the omy-mir-499ab copy, and therefore omy-mir-499aa paralogue represents the sum of both (omy-mir-499aa+ab).
miRNA expression during fast and slow myoblast culture development
Expression of mir-133 and mir-499 paralogues was studied in slow- and fast-derived myoblast cell cultures at days 6, 8 and 10 of development (Fig. 6). No significant differences in expression were found for any of the omy-mir-133 paralogues between slow and fast cell cultures (Fig. 6A–C). Between days 6 to 8, expression was 0.5-fold lower for omy-mir-499aa+ab and omy-mir-499bb and 0.6-fold lower for omy-mir-499ab in fast- compared with slow-derived myocytes (tissue P<0.01) (Fig. 6D–G). Omy-mir-499 copies did not show statistical differences during culture development (development P=0.62, 0.88, 0.86 and 0.94 for omy-mir-499aa+ab, omy-mir-499ab, omy-mir-499ba and omy-mir-499bb, respectively) (Fig. 6D–G).
Expression of omy-mir-133 and omy-mir-499 paralogues in response to electrical stimulation on slow muscle myoblasts were also investigated (Fig. 7). From the omy-mir-133 family, only omy-mir-133a-2 transcription significantly increased by 2-fold at day 6 of chronic stimulation (C-EPS group) (treatment P<0.05) (Fig. 7A–C). The expression of omy-mir-499ab at day 6 was 0.5-fold lower in C-EPS treated cells than in the CTR group (treatment P<0.05) (Fig. 7E). Omy-mir-499ba transcription was 7-fold higher at day 6 and 4-fold higher at day 8 (treatment P<0.001) in C-EPS treated cells compared with in the CTR group (Fig. 7F). The chronic stimulation also increased expression of the omy-mir-499bb paralogue, by 2.5-fold at day 6 (treatment P<0.001) and by 2-fold at day 8 (treatment P<0.01). In addition, omy-mir-499bb expression at day 6 was 2.3-fold higher in acute-stimulated myoblasts (A-EPS group) compared with in the CTR group (treatment P<0.01) (Fig. 7G).
To complement our results and provide further insight into miRNA paralogue roles, we performed correlation analyses between expression of omy-mir-133, omy-mir-499, smyhc, fmyhc and sox6 (Fig. S3). It is interesting to highlight the negative correlation between omy-mir-499 paralogues and sox6 (ρ=−0.38 for omy-mir-499aa+ab versus sox6; ρ=−0.5 for omy-mir-499ba versus sox6; ρ=−0.51 for omy-mir-499bb versus sox6), all of them significant (Fig. S3).
DISCUSSION
In the present study, we established a viable teleost slow myoblast cell culture, similar to the fast myoblast cell culture with some considerations: (1) the slow muscle is much firmer and very easy to lose during washes; (2) a layer of fat is formed during extraction that should be removed in order to increase cell yield; (3) after enzymatic digestion, slow muscle is especially rich in tissue debris and should be carefully filtered and washed; and (4) for an equivalent amount of tissue, slow muscle yields 43% more myoblasts than fast muscle (based on Neubauer chamber counting; data not shown). Unless the experimental design requires samples from the same animals, we recommend using small juveniles to extract fast skeletal muscle and larger animals for slow skeletal muscle. The difference in the number of myoblasts extracted from both tissues is in agreement with previous studies reporting a higher proportion of satellite cells in slow fibres (Gibson and Schultz, 1982) but with equivalent development stages as described for fast myoblast cell cultures (Fig. 1) (Bower and Johnston, 2010a; Castillo et al., 2006; Garcia de la serrana et al., 2014a).
Despite the morphological similarities between the slow and fast muscle cells, they were phenotypically different, as indicated by the expression profiles of six1, sox6, fmyhc and smyhc. Sox6 is a transcription factor that represses the slow fibre phenotype (Hagiwara et al., 2007), whereas Six1, another transcription factor, is required for the determination of the fast phenotype (Bessarab et al., 2008). Our results show that six1 and sox6 levels were significantly lower in slow myogenic cells, indicating that the slow program was not repressed (Fig. 2). Slow myogenic cells had a much higher expression of smyhc compared with fmyhc (Fig. 2). Our results suggest that myoblasts from slow and fast muscle tend to differentiate to the fibre type of the tissue they were extracted from, in agreement with a previous study on birds, where myoblasts extracted from the pectoralis major and anterior latissimus dorsi formed fast and slow myotubes in similar proportions as found in the muscle of origin (Feldman and Stockdale, 1991). It is interesting to note that slow muscle myogenic cells showed unexpectedly high levels of fmyhc (Fig. 2), raising questions about the possibility of some degree of phenotypic plasticity, i.e. turning into the fast phenotype in response to endocrine, nutritional or electrical signals.
We analyzed the expression of genes involved in different metabolic processes in order to gain a preliminary idea of the metabolic differences or similarities between slow and fast myoblasts. Many of the genes studied had a higher expression in the slow myoblasts (glut4, lamtor3, ragd and pgc1α), despite only pgc1α showing a statistically significant difference (Fig. 3). Pgc1α acts as a co-factor of mitochondrial biogenesis, and it is crucial to maintain slow muscle oxidative metabolism (Chan and Arany, 2014). Moreover, slow fibres might be significantly more insulin-responsive than fast fibres, owing to higher levels of the Glut4 protein (Kern et al., 1990), as inferred by a higher transcription of glut4 on slow myoblasts. The Lamtor/Rrag GTPases complex has been identified to act as an amino acid sensor and promote Mtor activation, representing an important mechanism through which amino acids stimulate protein synthesis by themselves (Demetriades et al., 2014; Sancak et al., 2010). Despite the similar expression pattern of rptor between fast and slow cultures, lamtor3 and ragd had higher transcription in slow myogenic cells (Fig. 3), suggesting a higher contribution of the Lamtor/Rrag GTPases complex to protein synthesis. The idea of an increase in protein synthesis during the progression of the cell culture is further supported by the expression of the E3 ubiquitin ligase mafbx, which was strongly inhibited in both tissues (Fig. 3) (Sandri, 2008).
We also used slow and fast muscle cell cultures as a model to characterize mir-133 and mir-499 families during differentiation and in response to electrostimulation. The miRNA mature sequences and secondary structures are highly conserved among different vertebrate species and between paralogues of the same family (Bizuayehu and Babiak, 2014). Phylogenetic analysis confirmed the identity of three mir-133 (omy-mir-133a-1a, omy-mir-133a-1b and omy-mir-133a-2) and four mir-499 (omy-mir-499aa, omy-mir-499ab, omy-mir-499ba and omy-mir-499bb) in rainbow trout, as expected after successive WGD. It is also interesting to highlight that rainbow trout seems to lack mir-133b and -133c, indicating a species-specific loss.
The omy-mir-133 paralogues had similar levels of expression between fast and slow myoblast cell cultures, with very little variation during development (Fig. 6). mir-133 has been described to be involved in muscle development by preventing myoblast differentiation and enhancing myoblast proliferation (Chen et al., 2006; Yu et al., 2014), which disagrees with the lack of transcriptional variation found in our study. Because mir-133 levels were unaffected in almost all conditions, expression of the target srf (serum responsive factor) was not determined in the present study. It might be possible that mir-133 has a different role in fish than that suggested in mammals, or that relevant changes occurred before day 6 of development, which was not included in the present work and would need further investigation.
The omy-mir-499 paralogues had higher abundance in slow myoblasts (Fig. 6), which is in agreement with the role of this miRNA promoting the slow fibre type phenotype (van Rooij et al., 2009; Wang et al., 2011). In both mammals (McCarthy et al., 2009; van Rooij et al., 2009) and teleost fish (Duran et al., 2015; Nachtigall et al., 2015; Wang et al., 2011), miR-499 mediates the translational repression of sox6, a putative target involved in the maintenance of the fast-twitch phenotype through the repression of slow-twitch-specific genes, such as slow myosin heavy chain 1 (von Hofsten et al., 2008). Our results show a negative correlation between several omy-mir-499 paralogues and sox6, suggesting that a similar mechanism might be in place in slow myoblast cell culture. These data are corroborated by the positive correlation between omy-mir-499ab and smyhc, as opposed to omy-mir-499bb and fmyhc (Fig. S3). In response to electrical stimulation, both mir-499b paralogues (omy-mir-499ba and omy-mir-499bb) increased their transcription after C-EPS treatment, indicating that mir-499b paralogues could be more susceptible to long-term electrical stimuli than mir-499a duplicates. Results from the C-EPS treatment suggest that the mir-499b paralogues might have an active role in slow fibre type specification and maintenance. However, considering the decreased expression of omy-mir-499ab at day 6 and a tendency of increased expression of omy-mir-499aa+ab at day 10 in C-EPS myoblasts (Fig. 7), another possibility could be that omy-mir-499b paralogues have an early role in slow phenotype determination, while omy-mir-499a copies may act in the late stage of myotube formation. Both possibilities suggest the sub-functionalization of omy-mir-499 paralogues, as a result of the teleost-specific WGD (Jaillon et al., 2004). Our study shows that omy-mir-499b paralogues probably retained only part of the original function of the omy-mir-499 gene, appearing to be more responsive to electrical signals and/or more involved in phenotype specification at early stages compared with omy-mir-499a copies. Evidence of the sub-functionalization of myod1 (myogenic differentiation factor 1) paralogues was also observed during myotube formation of Atlantic salmon muscle cells, with myod1a primarily expressed during cell differentiation and myod1b and 1c especially expressed during cell proliferation (Bower and Johnston, 2010a). Given the increased expression of mir-499b copies in the C-EPS group, we can conclude that chronic and slow-frequency stimulation enhanced the slow phenotype in cell culture and could be used in skeletal muscle fibre type studies.
The slow myoblast cell culture represents an interesting and useful in vitro model with which to study skeletal muscle. Particularities in processes such as muscle development, wasting and regeneration can be addressed in this system, in addition to modulation of muscle fibre phenotypes, such as studies investigating exercise and phenotypic plasticity. The cultured slow myoblasts offer the possibility for future manipulative and pharmacological experiments, including gain or loss of function assays that may provide new information about the roles of individual genes or signaling molecules. The next steps in the characterization of mir-133 and mir-499 paralogues in rainbow trout include the use of miRNA inhibitors and mimics to alter their expression and better define their function, which will increase the understanding of how these families regulate fish myogenesis.
Conclusions
We have successfully established a slow myoblast cell culture. The extraction of slow myoblasts opens the doors to future comparative studies between slow and fast muscle development, and regulation, as well as to study the physiology of the slow muscle. We have also characterized the members of the mir-133 and mir-499 family in rainbow trout and their expression profiles during myogenesis, confirming the role of mir-499 in slow muscle phenotype determination and casting doubts about the role of mir-133 during differentiation. In addition, we have found signs of sub-functionalization of mir-499 paralogues in response to electrostimulation.
Acknowledgements
We thank Professor Ian Alistair Johnston from the Scottish Oceans Institute (University of St Andrews) for hosting the present research in his laboratory facilities. We also thank Dr Robson Francisco Carvalho and Dr Edson Assunção Mareco for their valuable discussions.
Footnotes
Author contributions
Conceptualization: B.O.D., M.D., D.G.; Methodology: B.O.D., D.G.; Validation: B.O.D., D.G.; Formal analysis: B.O.D., D.G.; Investigation: B.O.D., D.G.; Resources: M.D., D.G.; Data curation: B.O.D., D.G.; Writing - original draft: B.O.D., D.G.; Writing - review & editing: B.O.D., M.D., D.G.; Visualization: B.O.D.; Supervision: M.D., D.G.; Project administration: M.D., D.G.; Funding acquisition: M.D.
Funding
This work received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. Funding was also provided by the National Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico; CNPq), with grants 447233/2014 and 302656/2015-4, and the São Paulo Research Foundation (Fundação de Amparo à Pesquisa do Estado de São Paulo; FAPESP), with grants 2015/03234-8, 2016/19683-9, 2016/05009-4 and 2019/01592-5. The funding agencies did not have roles in the design of the study, analysis of data or writing of manuscript, providing only the financial resources. D.G. is a Serra Húnter Tenure-Track Lecturer of the University of Barcelona.
Data availability
The datasets analyzed for this study can be found in the Ensembl Genome Browser 89 (http://www.ensembl.org/index.html), rainbow trout genome (https://www.genoscope.cns.fr/trout/) (Berthelot et al., 2014), SalmoBase (https://salmobase.org/) (Samy et al., 2017) and NCBI (http://www.ncbi.nlm.nih.gov).
References
Competing interests
The authors declare no competing or financial interests.