Skip to main content
Cambridge Open Access logoLink to Cambridge Open Access
. 2016 Oct 3;116(8):1315–1325. doi: 10.1017/S000711451600324X

Characterisation of equine satellite cell transcriptomic profile response to β-hydroxy-β-methylbutyrate (HMB)

Katarzyna A Szcześniak 1, Anna Ciecierska 1, Piotr Ostaszewski 1, Tomasz Sadkowski 1,*
PMCID: PMC5082287  PMID: 27691998

Abstract

β-Hydroxy-β-methylbutyrate (HMB) is a popular ergogenic aid used by human athletes and as a supplement to sport horses, because of its ability to aid muscle recovery, improve performance and body composition. Recent findings suggest that HMB may stimulate satellite cells and affect expressions of genes regulating skeletal muscle cell growth. Despite the scientific data showing benefits of HMB supplementation in horses, no previous study has explained the mechanism of action of HMB in this species. The aim of this study was to reveal the molecular background of HMB action on equine skeletal muscle by investigating the transcriptomic profile changes induced by HMB in equine satellite cells in vitro. Upon isolation from the semitendinosus muscle, equine satellite cells were cultured until the 2nd day of differentiation. Differentiating cells were incubated with HMB for 24 h. Total cellular RNA was isolated, amplified, labelled and hybridised to microarray slides. Microarray data validation was performed with real-time quantitative PCR. HMB induced differential expressions of 361 genes. Functional analysis revealed that the main biological processes influenced by HMB in equine satellite cells were related to muscle organ development, protein metabolism, energy homoeostasis and lipid metabolism. In conclusion, this study demonstrated for the first time that HMB has the potential to influence equine satellite cells by controlling global gene expression. Genes and biological processes targeted by HMB in equine satellite cells may support HMB utility in improving growth and regeneration of equine skeletal muscle; however, the overall role of HMB in horses remains equivocal and requires further proteomic, biochemical and pharmacokinetic studies.

Key words: β-Hydroxy-β-methylbutyrate, Satellite cells, Transcriptomic profile, Muscles, Horses


The domestic horse, Equus Caballus, is an evolutionary successor of grazing herbivores, whose survival was closely related to the speed and endurance necessary to escape predators and search for food. Since its domestication, man has used selective breeding to enhance performance capabilities of equids, so that they can fulfil their important role in human civilisation( 1 ). This has made the horse a valuable animal model for studying exercise physiology.

In modern days, the horse has become an extraordinary ‘athlete’, exercised for a broad range of sporting activities (racing, endurance rides, show jumping, dressage, 3-d eventing, heavy draught work, polo, reining, cutting and competitive driving, as well as pleasure riding)( 1 ), which may be associated with serious muscle overloading and an increased risk of injuries. This concerns especially the top-level competitors that are exposed to maximal training loads to achieve even a tiny increase in performance; however, even this small edge over competitors may result in winning the competition( 2 ).

This explains the growing demand for alternative treatments that may help improve equine muscle performance and avoid injury. One of these is supplementation with β-hydroxy-β-methylbutyrate (HMB), a metabolite of the essential branched-chain amino acid leucine( 3 ). The benefits of HMB supplementation on muscle metabolism have been demonstrated in various species, under physiological as well as pathological conditions( 3 , 4 ). Previous studies have indicated that HMB may affect muscle metabolism and growth by at least six different mechanisms of action, including attenuation of protein degradation( 5 ), increased protein synthesis( 6 ), protection of sarcolemma( 7 ), inhibition of apoptosis( 8 ), enhancement of somatotrophic axis function( 9 ) and myogenic cell activation( 10 ). Recent evidence has indicated additional benefits of HMB supplementation related to energy metabolism, including improved aerobic performance( 11 ) as well as increased fat loss with exercise( 12 ); however, the underlying mechanisms are poorly understood.

Despite the large amount of literature linked to HMB, only two reports have supported anecdotal data showing HMB’s benefits in thoroughbred racing horses. In one of them, exercising thoroughbred race horses receiving daily 15 g Ca salt of HMB during a 16-week training season showed a significant decrease in post-exercise blood creatinine phosphokinase and lactate levels over both training and racing seasons( 13 ). Miller et al.( 14 ) observed similar results when supplementing racing horses with 10 g of HMB daily, with a significantly improved win rate after the 1st month of racing. Taken together, the present experiment meets the demand for more detailed studies concerning HMB’s effectiveness in horses.

In adult skeletal muscle, regeneration and hypertrophy depend on the activation of mononucleated, muscle precursor cells called satellite cells (SC)( 15 ), embedded between the sarcolemma and the basement membrane of muscle fibres. Previous in vitro and in vivo studies indicate that HMB may activate SC( 8 , 10 , 16 , 17 ), but the mechanism underlying this action remains unclear. Some evidence suggests that HMB regulates the expression of myogenesis-related genes( 8 ); however, until now, no one has demonstrated any effect of HMB on global gene expression.

The horse is a valuable animal model for studying exercise physiology. Gene expression determines most of the phenotype; therefore, the present study focused on revealing the molecular background of HMB action in equine skeletal muscle by investigating the impact of HMB on global gene expression in differentiating equine satellite cells (ESC) in vitro. To our knowledge, this is the first study where HMB’s trancriptomic profile was described. This in vitro model can help identify and better understand the potential therapeutic options to promote muscle regeneration and energy metabolism in horses and other mammals.

Methods

Cell culture

Media and reagents

The following materials were used during cell culture: the Ca salt (monohydrate) of HMB (Ca-HMB) was purchased from Metabolic Technologies; Dulbecco’s Modified Eagle Medium (DMEM) (1×) with glutamax, fetal bovine serum (FBS), horse serum (HS) and antibiotics (AB) penicillin–streptomycin and fungizone – were purchased from Gibco, Life Technologies; penicillium crystalicum (AB) was purchased from Polfa Tarchomin; PBS, protease from Streptomyces griseus and DMSO were purchased from Sigma Aldrich. Tissue culture flasks Primaria (25, 75 cm2) and Collagen I Cellware six-well plates were purchased from Becton Dickinson. Ca-HMB was transformed to the acid form by acidification with 1 N-HCl. HMB was then extracted four times with diethyl ether. The pooled organic layer was dried under vacuum for 24 h at 38 °C. The resulting free acid was 99 % HMB as assessed by HPLC.

Muscle sampling and satellite cells isolation

Semitendinosus muscle samples were collected ex vivo from six horses (6-month-old, healthy colts). Muscle sampling and ESC isolation are described in detail by Szcześniak et al.( 18 ). In brief, semitendinosus muscle samples were dissected free of surrounding tissues, sliced, washed in PBS with decreasing antibiotics concentration, suspended in FBS with 10 % DMSO, cooled to −80°C and stored in liquid N2. Before isolation, the samples were thawed, centrifuged and washed three times with PBS along with antibiotics. Samples were incubated with DMEM/AB/protease from S. griseus and sieved in order to separate tissue debris. The filtrates were centrifuged three times, re-suspended in proliferation medium (10 %FBS/10 %HS/DMEM/AB) and transferred to polypropylene Petri culture disks. One-and-a-half hours of preplating was performed to minimise possible fibroblast contamination. Subsequently, the supernatant containing ESC was transferred to Primaria culture flasks.

Cell culture and experimental design

The experimental design is presented in Fig. 1. Upon isolation, samples of ESC (n 6) were incubated for 10 d in Primaria culture flasks. The proliferation medium was changed every 2 d. On the 10th day, cells were trypsinised, and 30 000 cells (counted by Scepter Cell Counter; Merck Millipore) from each flask were transferred to the respective wells of two six-well plates. One plate was dedicated to HMB treatment and one served as the control. After obtaining 80 % of confluence, the proliferation medium was replaced with a differentiation medium (2 % HS/DMEM/AB). Immediately after 48 h of differentiation, the medium from one plate was replaced by a differentiation medium containing 50 µm of HMB, whereas in the second plate the standard differentiation medium was used as a control. After 24 h, the medium from each plate was discarded, plates were washed with PBS and stored at −80°C until further analysis. The concentration of HMB was based on the available literature values and cell viability colourimetric assay test with 3-(4,5-dimethylthiazol-2-yl)-2-5-diphenyltetrazolium bromide (data not shown).

Fig. 1.

Fig. 1

Experiment design. Equine satellite cells (ESC) were cultured until they reached 80 % confluence; next, the proliferation medium was replaced with a differentiation medium. After the 2nd day of differentiation, cells were incubated for 24 h with β-hydroxy-β-methylbutyrate (HMB). Following the HMB treatment, differentiating cells were scraped and stored at −80°C until further analysis.

Microarray analysis and real-time quantitative PCR validation

RNA isolation, validation, labelling hybridisation and microarray analysis

Total RNA from HMB and control cells was isolated according to the protocol supplied with the miRNeasy Mini Kit (Qiagen). RNA quantity was measured spectrophotometrically using NanoDrop (NanoDrop Technologies). The analysis of final RNA quality and integrity was performed with BioAnalyzer 2100 (Agilent Technologies). To ensure optimal microarray data quality, only samples with the highest RNA integrity number (RIN)≥9·2 were included in the analysis.

Analysis of gene expression profiles was performed using Horse Gene Expression Microarray, 4×44K (Agilent Technologies). Low Input Quick Amp Labeling Kit (Agilent Technologies) was used to amplify and label total RNA (100 ng) to generate complementary RNA (cRNA). On each two-colour microarray, 825 ng of cRNA from HMB-exposed cells (labelled by Cy5, n 4) and 825 ng of cRNA from control cells (labelled by Cy3, n 4) were hybridised to the arrays (Gene Expression Hybridization Kit; Agilent Technologies) according to the manufacturer’s protocol.

RNA Spike-In Kit (Agilent Technologies) was used as an internal control to efficiently monitor microarray workflow for linearity, sensitivity and accuracy. Acquisition and analysis of hybridisation intensities were performed using the DNA microarray scanner (Agilent Technologies) and Feature Extraction software 10.7.3.1 according to the standard manufacturer’s procedures. Linear Lowess was applied for data normalisation and Cy5/Cy3 dye bias compensation.

Statistical analysis

Statistical analysis was performed using Gene Spring 13 software (Agilent Technologies) with the default setting for two-colour microarrays. The estimated significance level (P value) was corrected for multiple hypotheses testing using the Benjamini and Hochberg false discovery rate (FDR) adjustment. mRNA with FDR≤0·05 were selected as significantly differentially expressed genes (DEG).

The microarray experiment was performed according to Minimum information about a microarray experiment (MIAME) guidelines( 19 ). The data discussed in this publication have been deposited in National Center for Biotechnology Information’s (NCBI’s) Gene Expression Omnibus (GEO)( 20 ) and are accessible through GEO Series accession number GSE74495 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE74495).

Complementary DNA synthesis and real-time quantitative PCR

To independently assess expression changes for a selected group of genes obtained from the microarray data, the real-time quantitative PCR (RT-qPCR) method was applied. The sequences of verified genes, complementary to those on microarrays, were obtained from Ensembl database. Primers were designed using Primer-Blast software (NCBI database) and then checked for secondary structures using the Oligo Calculator (http://www.basic.northwestern.edu/biotools/oligocalc.html). The secondary structures of the amplicon were examined using m-fold Web Server (http://mfold.rna.albany.edu/?q=mfold). The sequences of primers are listed in Table 1. The primers were purchased from Oligo IBB (Polish Academy of Science). Each primer pair was quality tested to ensure that a single product was amplified (dissociation curve analysis) and that there was no primer–dimer coupling.

Table 1.

Sequences of primers used for real-time quantitative PCR

No. Gene symbol Forward primer Reverse primer Annealing temperature (ºC) Product lenght
1 Cfl2 CCCGCAGAGTTGACACAATA TGTGGCATCGTACAAAGCAT 60 282
2 Myf5 GGAGACGCCTGAAGAAAGTC CCGGCAGGCTGTAGTAATTC 60 171
3 Rbfox GAACCAGGAGGGATCTTCCA TTGCCATACACAGGCTCTTG 60 213
4 S1pp1 CCCAAGTCAGTCCAACGAAA GGCACAGCTGGTGTAAAAAC 60 143
5 Tgfb2 AGTACTACGCCAAGGAGGTT TAGGCGGGATGGCATTTTCC 60 72
6 Trim63 AAGGAGGCAGCCAGGTAGAG CACGGACACTGAGCCACTTC 62 220
7 Gapdh GTTTGTGATGGGCGTGAACC GTCTTCTGGGTGGCAGTGAT 60 198

Cfl2, coffilin 2; Myf5, myogenic factor 5; Rbfox, RNA binding protein, fox-1 homolog C. elegans; S1pp1, secreted phosphoprotein 1; Tgfb2, transforming growth factor, β2; Trim63, muscle-specific RING finger protein 1; Gapdh, glyceraldehyde 3-phosphate dehydrogenase.

A quantity of 1 µg of total RNA from HMB-treated and control cells (n 6) was reverse transcribed using a Transcription First Strand cDNA Synthesis Kit (Agilent Technologies). All analyses were performed on individual samples of total RNA using a SensiFAST SYBR lo-ROX Kit (Blirt, Bioline) following the manufacturer’s protocol. Assays for each gene were conducted in duplicate in a Stratagene Mx3005p thermal cycler (Agilent Technologies) according to the following protocol: pre-incubation for 2 min at 95°C and amplification (forty cycles), with denaturation at 95°C for 5 s and annealing at the temperatures specified in Table 1 for 15 s. The dissociation curve setting was as follows: denaturation at 95°C for 0 s, annealing (at the temperatures specified in Table 1), continuous melting up to 95°C for 0 s (slope=0·1°C/s) and cooling at 40°C for 30 s. Glyceraldehyde 3-phosphate dehydrogenase (Gapdh) was used as a reference gene. The relative expression of the target gene was calculated according to the following formula:

graphic file with name S000711451600324X_eqnU1.jpg

where ΔC Inline graphic is the difference in C T between the targeted gene and the reference control. Results were calculated as Inline graphic using GenEx 6.0 (MultiD Analyses)( 21 ). The amplification efficiency (E=10(−1/slope)–1) was determined using a comparative quantitation standard curve and was >0·9 for each target gene and the reference gene. Standard curves were generated using a four-point 1:10 dilution series starting with cDNA representing 10 ng of input total RNA. RT-qPCR analysis was conducted according to a standardised approach( 22 ).

Functional analysis

The list of DEG was examined by the Functional Analysis tool in the Database for Annotation, Visualization and Integrated Discovery (DAVID version 6.7) to assign them to gene ontology (GO) terms and KEGG pathways (Kyoto Encyclopedia of Genes and Genomes)( 23 ). Human background was used for this analysis, because far more human genes are annotated and more information in databases is available for humans than for horses. Enrichment of DEG was calculated by EASE score (modified Fisher exact test). For further analysis and visualisation of data, the Pathway Studio Web Mammalian was used. This database of functional relationships between mammalian proteins is compiled using Med Scan technology from over twenty-four million PubMed abstracts and over 3·5 million Elsevier full-text papers. All identified relations were filtered by reference count (≥2) to ensure maximal confidence levels, which means that the number of publications confirming each relationship was ≥2.

Results

Microarray analysis

Analysis of gene expression between HMB-treated and control cells revealed statistically significant (FDR≤0·05) differences in the case of 627 records. Within them were 361 unduplicated, identified transcript ID including 159 up- and 202 down-regulated DEG, in the HMB v. the control group. All array data are plotted and shown in the online Supplementary Material S1. Table 2 presents genes selected for discussion, presumably involved in HMB action on ESC.

Table 2.

List of selected differentially expressed genes in β-hydroxy-β-methylbutyrate-treated v. control equine satellite cells (false discovery rate≤0·05, n 4)

No. Gene symbol Fold change Description False discovery rate (corrected p-value)
1 Nos2 −2·43 Inducible nitric oxide synthase (NM_001081769) 4·34E–2
2 Myf5 −2·09 Myogenic factor 5 (ENSECAT00000021416) 4·63E–2
3 Dmd −2·06 Dystrophin (ENSECAT00000023688) 3·18E–2
4 Trim63 −2·02 Tripartite motif containing 63, E3 ubiquitin protein ligase (ENSECAT00000026380) 4·96E–2
5 Itgb1bp2 −1·94 Integrin β 1 binding protein (melusin) 2 (ENSECAT00000016364) 4·52E–2
6 Saa1 −1·88 Serum amyloid A1 (ENSECAT00000013971) 4·96E–2
7 Tagln3 −1·80 Transgelin 3 (ENSECAT00000010210) 4·73E–2
8 Tgfb2 −1·75 Transforming growth factor, β2 (XM_003364564·2) 3 31E–2
9 Murc −1·69 Muscle-related coiled-coil protein (ENSECAT00000006670) 4·76E–2
10 Svil −1·66 Supervillin (XM_014737013·1) 4·88E–2
11 Lama2 −1·60 Laminin, α5 (XM_014735356·1) 3·18E–2
12 Mef2c −1·56 Myocyte enhancer factor 2 C (XM_014857076·1) 3·56E–2
13 Lama2 −1·42 Laminin, α2 (ENSECAT00000025657) 3·96E–2
14 Prkab2 −1·42 Protein kinase, AMP-activated, β2 non-catalytic subunit (XM_008509324·1) 4·65E–2
15 Mef2a −1·32 Myocyte enhancer factor 2A (XM_011521571·1) 4·76E–2
16 Ppargc1b −1·22 PPAR-γ coactivator (ENSECAT00000021080) 4·75E–2
17 Cul3 −1·17 Cullin 3 (ENSECAT00000012128) 4·67E–2
18 Esrra −1·13 Oestrogen-related receptor α (ENSECAT00000016651) 4·31E–2
19 Zfp91 −1·10 Zinc finger protein 91 homolog (XM_005598160) 3·95E–2
20 Abca1 1·79 ATP-binding cassette, sub-family A, member 1 (XM_001493790) 3·87E–2
21 Mapk14 1·75 Mitogen-activated protein kinase 14 (XM_005604060) 4·89E–2
22 F2rl2 1·65 Coagulation factor II (thrombin) receptor-like 2 (ENSECAT00000010830) 4·49E–2
23 Fads1 1·33 Fatty acid desaturase 1 (XM_008510001) 4·96E–2
24 Abhd5 1·24 Anhydrolase domain containing 5 (ENSECAT00000023610) 3·96E–2

Real-time quantitative PCR

According to the ontological classification and the literature, six genes – Cfl2 (coffilin 2, muscle), Myf5 (myogenic factor 5), Rbfox (RNA binding protein, fox-1 homolog C. elegans), S1pp1 (secreted phosphoprotein 1), Tgfb2 (transforming growth factor, β2) and Trim63 (muscle-specific RING finger protein 1) involved in the skeletal muscle development – were selected for RT-qPCR validation. Expression changes from RT-qPCR data overlapped microarray results and are presented in Fig. 2.

Fig. 2.

Fig. 2

Genes selected for real-time quantitative PCR (RT-qPCR) validation of microarray results: Cfl2 (coffilin 2, muscle), Myf5 (myogenic factor 5), Rbfox (RNA binding protein, fox-1 homolog C. elegans), S1pp1 (secreted phosphoprotein 1), Tgfb2 (transforming growth factor, β2) and Trim63 (muscle-specific RING finger protein 1). Expression changes from RT-qPCR data overlapped microarray results. * P≤0·05, ** P≤0·01, *** P≤0·001 are significant (n 6). Inline graphic, β-hydroxy-β-methylbutyrate (HMB); Inline graphic, Ctrl.

Functional analysis

DAVID functional analysis assigned DEG to seventy-five biological processes (BP), eleven cellular components and ten molecular functions as well as four KEGG pathways (EASE score P<0·05). All GO considered significant are shown in the online Supplementary Material S2. KEGG pathways and the most significantly enriched (EASE score <0·01) GO retrieved from DAVID are presented in Table 3, providing a comprehensive overview of important processes, most likely induced by HMB in differentiating ESC.

Table 3.

Functional analysis of differentially expressed genes*

GO
Categories Term Count % P Genes
Biological process GO:0007517 – muscle organ development 14 4·12 2·31E–4 Mef2c, Mef2a, Myf5, Tagln3, Tgfb2, Lama2, Zfp91, Murc, Lama5, Mapk14, Svil, Dmd, Itgb1bp2, F2r
Cellular component GO:0005829 – cytosol 46 13·53 3 84E–4 Bcat1, Alad, Ggct, Tnfrsf25, Abhd5, Kcnip3, Rps3, Cep70, Zfp91, Rps26, Bag1, Slmap, Hnrnpd, Gucy1a3, Eif3i, Nos2, Rpia, Psmd6, Plcb1, Gchfr
Biological process GO:0009987 – cellular process 227 66·76 5·32E–4 Mef2c, Mef2a, Alad, Tars2, Fst, Gfer, Lpar2, Edil3, Rest, Tpd52, Prkg1, S1pr2, Cul3, Zfp91, Hmcn1, Kifap3, Sfrs9, Scd5, Nsmaf, Rpp21
Biological process GO:0048518 – positive regulation of biological process 58 17·06 1·94E–3 Mef2c, Fosl2, Fst, Tlr1, Lpar2, Pmaip1, Edil3, Gli1, Tgfb2, Rps3, Cul3, S1pr2, Zfp91, Mll5, Ang, Saa1, Kifap3, Gucy1a3, Nos2, Psmd6
Biological process GO:0050793 – regulation of developmental process 25 7·35 2·80E–3 Gna12, Fst, Abca1, Rest, Gli1, Tgfb2, Zfp91, Cdc42ep3, Nkx2-2, Spp1, B4galt1, Esrra, Foxj1, Fads1, Smad5, Mgp, Ski, Smad1, Sod2, Lama2…
Biological process GO:0044267 – cellular protein metabolic process 64 18·82 3·37E–3 Gnptg, Cdk19, Ilkap, Tars2, Kiaa0368, Lpar2, Prkg1, Ttll1, Tgfb2, Rps3, S1pr2, Cul3, Mll5, Hmcn1, Pak3, Map1lc3b, Aak1, Slmap, St3gal6, Stk39
Biological process GO:0030278 – regulation of ossification 7 2·06 3·90E–3 Esrra, Smad5, Mgp, Gdf10, Ski, Smad1, Tgfb2
Biological process GO:0051239 – regulation of multicellular organismal process 31 9·12 4·27E–3 Tlr1, Fst, Rest, Tpm3, Kcnmb2, Tgfb2, Gli1, Zfp91, chd7, Saa1, Arg2, Gucy1a3, Nos2, Kcnq1, Nkx2-2, Spp1, B4galt1, Esrra, Foxj1, Smad5
Biological process GO:0030155 – regulation of cell adhesion 9 2·65 5·05E–3 Lama2, Cytip, Saa1, Lama5, Kifap3, Myf5, Edil3, Spp1, Tgfb2
Biological process GO:0048522 – positive regulation of cellular process 51 15·00 7·59E–3 Mef2c, Fosl2, Tlr1, Lpar2, Pmaip1, Edil3, Tgfb2, Gli1, Rps3, Cul3, S1pr2, Zfp91, Mll5, Saa1, Ang, Kifap3, Gucy1a3, Psmd6, Samd4a, Ip6k2
Biological process GO:0051345 – positive regulation of hydrolase activity 10 2·94 7·94E–3 Uaca, Ang, Gnb1, Foxj1, Abhd5, Arhgap27, Lpar2, Pmaip1, Rps3, F2r
Biological process GO:0009891 – positive regulation of biosynthetic process 24 7·06 8·19E–3 Mef2c, Esrra, Tp53bp1, Myf5, Smad5, Tlr1, Abca1, Smad1, Ppargc1b, Sod2, Gli1, Tgfb2, Murc, Mll5, Mapk14, Gucy1a3, Prkaa1, Hoxb9, Rnf10, Smarca2, Nfatc3, Nkx2-2, Samd4a, F2r
Cellular component GO:0022627 – cytosolic small ribosomal subunit 5 1·47 8·49E–3 Rps26, Rps18, Rps14, Rps12, Rps3
Biological process GO:0060341 – regulation of cellular localisation 12 3·53 8·78E–3 B4galt1, Zfp91, Uaca, Chd7, Saa1, Ang, Pkig, Fst, Nos2, Kcnq1, Calm1, Tgfb2
Cellular component GO:0015935 – small ribosomal subunit 6 1·76 8·88E–3 Rps26, Rps18, Rps14, Mrps24, Rps12, Rps3
Molecular functions GO:0030145 – manganese ion binding 9 2·65 9·69E–3 B4galt1, Ilkap, B4galt3, Arg2, Smg1, Ppp1cc, B4galt7, Galnt12, Sod2
KEGG pathways
Terms Count % P Genes
hsa01040: biosynthesis of unsaturated fatty acids 4 1·18 1·0E–2 Acot7, Fads1, Hacd1, Scd5
hsa00601: glycosphingolipid biosynthesis 4 1·18 2·0E–2 B4galt1, B4galt3, B3gnt5, St3gal6
hsa04270: vascular smooth muscle contraction 7 2·06 4·0E–2 Gna12, Gucy1a3, Prkg1, Ppp1cc, Plcb1, Calm1, Kcnmb2
hsa05410: hypertrophic cardiomyopathy 6 1·76 4·0E–2 Lama2, Dmd, Prkab2, Prkaa1, Tgfb2, Tpm3

GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; Aak1, AP2 associated kinase 1; Abca1, ATP-binding cassette, sub-family A, member 1; Abhd5, abhydrolase domain containing 5; Acot7, acyl-CoA thioesterase 7; Alad, aminolevulinate dehydratase; Ang, angiogenin, ribonuclease, RNase A family, 5; Arg2, arg2; Arhgap27, rho GTPase activating protein 27; B3gnt5, β-1,3-N-acetylglucosaminyltransferase 5; B4galt1, β-1,4-galactosyltransferase 1; B4galt3, β-1,4-galactosyltransferase 3; B4galt7, β-1,4-galactosyltransferase 7; Bag1, BCL2 associated athanogene 1; Bcat1, branched chain amino acid transaminase 1; Calm1, calmodulin 1 (phosphorylase kinase, delta); Cdc42ep3, CDC42 effector protein 3; Cdk19, cyclin-dependent kinase 19; Cep70, centrosomal protein 70; Chd7, chromodomain helicase DNA binding protein 7; Cul3, cullin 3; Cytip, cytohesin 1 interacting protein; Dmd, dystrophin; Edil3, EGF Like repeats and discoidin domains 3; Eif3i, eukaryotic translation initiation factor 3 subunit I; Esrra, estrogen related receptor α; F2r, coagulation factor II thrombin receptor; Fads1, fatty acid desaturase 1; Fosl2, FOS like antigen 2; Foxj1, forkhead box J1; Fst, follistatin; Galnt12, polypeptide N-acetylgalactosaminyltransferase 12; Gchfr, GTP cyclohydrolase I feedback regulator; Gdf10, growth differentiation factor 10; Gfer, growth factor, augmenter of liver regeneration; Ggct, γ-glutamylcyclotransferase; Gli1, GLI family zinc finger 1; Gna12, G protein subunit α 12; Gnb1, G protein subunit β 1; Gnptg, N-acetylglucosamine-1-phosphate transferase γ subunit; Gucy1a3, guanylate cyclase 1, soluble, α 3; Hmcn1, hemicentin 1; Hnrnpd, heterogeneous nuclear ribonucleoprotein D; Hoxb9, homeobox B9; Ilkap, ILK associated serine/threonine phosphatase; Ip6k2, inositol hexakisphosphate kinase 2; Itgb1bp2, integrin subunit β 1 binding protein 2; Kcnip3, potassium voltage-gated channel interacting protein 3; Kcnmb2, potassium calcium-activated channel subfamily M regulatory β subunit 2; Kcnq1, potassium voltage-gated channel subfamily Q member 1; Kiaa0368, ECM29 homolog, proteasome accessory protein; Kifap3, kinesin associated protein 3; Lama2; laminin subunit α 2; Lama5, laminin subunit α 5; Lpar2, lysophosphatidic acid receptor 2; Map1lc3b, microtubule associated protein 1 light chain 3 β; Mapk14, mitogen-activated protein kinase 14; Mef2a, myocyte enhancer factor 2A; Mef2c, myocyte enhancer factor 2C; Mgp, matrix Gla protein; Mll5, lysine methyltransferase 2E; Mrps24, mitochondrial ribosomal protein S24; Murc, muscle related coiled-coil protein; Myf5, myogenic factor 5; Nfatc3, nuclear factor of activated T-cells 3; Nkx2-2, NK2 homeobox 2; Nos2, nitric oxide synthase 2; Nsmaf, neutral sphingomyelinase activation associated factor; Pak3, P21 protein (Cdc42/Rac)-activated kinase 3; Pkig, protein kinase (CAMP-dependent, catalytic) inhibitor γ; Plcb1, phospholipase C β 1; Pmaip1, phorbol-12-myristate-13-acetate-induced protein 1; Ppargc1b, PPARG coactivator 1 β; Ppp1cc, protein phosphatase 1 catalytic subunit γ; Prkaa1, protein kinase AMP-activated catalytic subunit α 1; Prkab2, protein kinase AMP-activated non-catalytic subunit β 2; Prkg1, protein kinase, CGMP-dependent, type I; Psmd6, proteasome 26S Subunit, Non-ATPase 6; Ptpla, 3-hydroxyacyl-CoA dehydratase 1; Rest, RE1 silencing transcription factor; Rnf10, ring finger protein 10; Rpia, ribose 5-phosphate isomerase A; Rpp21, ribonuclease P/MRP subunit P21; Rps12, ribosomal protein S12; Rps14, ribosomal protein S14; Rps18, ribosomal protein S18; Rps26, ribosomal protein S26; Rps3, ribosomal protein S3; S1pr2, sphingosine-1-phosphate receptor 2; Saa1, serum amyloid A1; Samd4a, sterile α motif domain containing 4A; Scd5, stearoyl-CoA desaturase 5; Sfrs9, serine/arginine-rich splicing factor 9; Ski, SKI proto-oncogene; Slmap, sarcolemma associated protein; Smad1, SMAD family member 1; Smad5, SMAD family member 5; Smarca2, SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 2; Smg1, SMG1 phosphatidylinositol 3-kinase-related kinase; Sod2, superoxide dismutase 2, mitochondrial; Spp1, secreted phosphoprotein 1; St3gal6, ST3 β-galactoside α-2,3-sialyltransferase 6; Stk39, serine/threonine kinase 39; Svil, supervillin; Tagln3, transgelin 3; Tars2, threonyl-TRNA synthetase 2, mitochondrial (putative); Tgfb2, transforming growth factor β 2; Tlr1, toll like.

*

Most significantly enriched ontologies (P<0·01) and KEGG pathways are presented.

Using Pathway Studio Web Mammalin Build Pathway Wizard Find Direct Links, we depicted all genes discussed in the present study that can directly or indirectly affect skeletal muscle cell functions (Fig. 3). Moreover, Pathway Studio Web Mammalian Build Pathway Wizard Find Common Targets algorithm allowed us to identify cell processes regulated by at least two of the DEG according to literature data. This resulted in fifty-six identified targets; among these, the twelve regulated by the highest number of genes were considered to be the most important for the HMB effect on ESC. A chart presenting these processes is presented in Fig. 4. From all targeted cell processes, we selected the most important relationships and are presented in Fig. 5. The online Supplementary Material S3 contains details of all identified relationships between DEG and cell processes.

Fig. 3.

Fig. 3

Pathway depicting β-hydroxy-β-methylbutyrate (HMB)-modulated genes identified in the present analysis, which could directly or indirectly affect skeletal muscle cell functions. This pathway was created using Pathway Studio Web Mammalian. Genes are marked with red and blue colour for up- and down-regulation, respectively. F2R, coagulation factor II; SAA1, serum amyloid A1; TAGLN3, transgelin 3; SVIL, supervilin; MEF2a and MEF2c, myocyte enhancer factor 2a and 2c; TGFB2, transforming growth factor, β2; MAPK14, mitogen-activated protein kinase 14; ZFP91, zinc finger protein 91 homolog; MYF5, myogenic factor 5; HACD1, 3-hydroxyacyl-CoA dehydratase 1 (alias PTPLA); LAMA, laminins; MURC, muscle-related coiled-coil protein; DMD, dystrophin; ITGB1BP2, integrin β1 binding protein (melusin) 2; Inline graphic, direct regulation; Inline graphic, expression; Inline graphic, promoter modification; Inline graphic, regulation.

Fig. 4.

Fig. 4

Major cell processes regulated by differentially expressed genes (DEG) between β-hydroxy-β-methylbutyrate and control cells. Analysis was performed using Pathway Studio Web Mammalian. Only relations with confidence levels ≥2 were included in the analysis. Details of all identified relationships between DEG and targeted cell processes are contained in the online Supplementary Material S3.

Fig. 5.

Fig. 5

Relevance network over-viewing discussed relationships between β-hydroxy-β-methylbutyrate (HMB)-modulated genes and cell processes (Pathway Studio Web Mammalian). Genes are marked with red and blue colour for up- and down-regulation, respectively. F2R, coagulation factor II; SAA1, serum amyloid A1; NOS2, nitric oxide synthetase, inducible, 2; MEF2a and MEF2c, myocyte enhancer factor 2a and 2c; TGFB2, transforming growth factor, β2; DMD, dystrophin; Trim63, muscle-specific RING finger protein 1; ESRRA, oestrogen-related receptor α; ABHD5, abhydrolase domain-containing protein 5; PRKAB2, protein kinase, AMP-activated, β2 non-catalytic subunit; CUL3, cullin 3; LAMA2, laminins; MURC, muscle-related coiled-coil protein; MYF5, myogenic factor 5; ABCA1, ATP-binding cassette, sub-family A, member 1; PPARGC1B, peroxisome proliferator-activated receptor γ, coactivator 1 β; B4GALT1, β-1,4-galactosyltransferase 1; ST3GAL6, ST3 β-galactoside α-2,3-sialyltransferase 6; B4GALT3, β-1,4-galactosyltransferase 3; Inline graphic, expression; Inline graphic, promoter binding; Inline graphic, promoter modification; Inline graphic, regulation.

Discussion

The objective of the present study was to identify the molecular background of HMB action on equine skeletal muscle. In order to cover all the salient points of functional analysis, only relations significant in DAVID and possessing the highest reference number in Pathway Studio analysis were considered to be important. To date, no official genome nomenclature has been established for the horse. According to the guidelines published by The International Society for Animal Genetics, for all genes with human orthologues, official human gene symbols (Human Genome Organisation (HUGO) Gene Nomenclature Committee) are applied.

We decided to use a primary SC model because of its stem cell potential. SC are able to differentiate into multiple mesenchymal lineages( 24 ) and to self-renew( 25 ), because of which they maintain extraordinary regenerative properties of skeletal muscles. However, the capacity of SC to proliferate and differentiate may vary depending on the origin of the muscle( 26 ), cell surface markers expression( 27 ), myogenic regulatory factors (MRF) expression( 28 ) and muscle fibre type( 29 ). In our study, all samples of ESC were isolated from semitendinosus muscle, which in horses is composed mainly of type II fast-twitch fibre muscle( 30 ). SC originating from this type of muscle may have less adipogenic properties compared with SC from type I fibres( 29 ). Heterogeneity of the SC could limit in vivo significance of the data obtained in the present study.

In general, the present analysis underlined the role of HMB as a global regulator, which is shown by the strong over-representation of genes linked to the BP: ‘regulation of developmental process’ and ‘positive regulation of BP’. Moreover, functional analysis revealed significant enrichment in ontology terms associated with cellular responses (Table 3). The three main cellular processes include cell proliferation, apoptosis and differentiation, which suggest that HMB is an important cell growth regulator (Fig. 4 and 5).

In adult skeletal muscle, extracellular matrix proteins anchor SC between the basal lamina and the apical sarcolemma, which create a specialised micro-environment called a stem cell niche. It is able to produce factors controlling stem cell behaviour( 31 ). Impaired adhesion of SC to their niche can stimulate proliferation( 32 ). Thereby, enrichment of the terms ‘regulation of cell adhesion’ and ‘cellular localisation’ may suggest HMB’s ability to indirectly control ESC proliferation by affecting their localisation in the niche.

Muscle development

The term ‘muscle organ development’ is the most significantly enriched annotation among genes regulated in ESC exposed to HMB (Table 3). This indicates that at least at the mRNA level HMB may affect muscle development (summarised on Fig. 3). A total of fourteen DEG were annotated to this term; however, among them, Mapk14 (mitogen-activated protein kinase 14) possessed the highest potential to regulate other genes and cell processes (Fig. 3 and 5). Mapk14 is activated by extracellular stimuli such as pro-inflammatory cytokines or physical stress, leading to direct activation of multiple cellular processes such as proliferation, differentiation, apoptosis and transcription regulation( 33 ). In SC, phosphorylation of MAPK14 may induce initiation( 34 , 35 ) or withdrawal( 36 ) from the cell cycle. The second can lead either to terminal differentiation or to programmed cell death( 37 ) depending on the nature of the stimulant and cell type. In vitro studies suggest that the two isoforms of Mapk14, p38α and p38β, appear to have different effects on cardiomyocyte hypertrophy: p38β seems to be more potent in inducing hypertrophy, whereas p38α appears to be more important in apoptosis( 38 ). The contribution of Mapk14 in cellular responses to HMB has already been reported by Kornasio et al.( 8 ), who suggested that the MAPK/ERK pathways mediate HMB’s effects on myoblast proliferation. HMB-related increase in phosphorylation of MAPK14 was also observed in dexamethasone-induced muscle atrophy in rats( 39 ).

Except for its ability to influence multiple cell processes, Mapk14 was reported to regulate many other genes from the analysis. One of them is Nos2 (nitric oxid synthase 2, inducible), interesting because of its lowest expression among all genes. Nos2 gene expression may be activated by Mapk14; however, it is assigned to shock signalling in inflammatory cells( 40 ) and its biological meaning in ESC remains unclear. Down-regulation of this gene by HMB has already been presented by Mitsutaka et al.( 41 ) in lipopolysaccharide-treated murine macrophages. This considered together may suggest an anti-inflammatory component of HMB action. Mapk14-dependent phosphorylation of transcription factors Mef2a and Mef2c (myocyte enhancer factor 2a and 2c) has been implicated in stress activation of immune, skeletal and cardiac muscle cells( 42 , 43 ). Among genes identified in our study, Mapk14 posseses two upstream promoters, Saa1 (serum amyloid A1) and F2r (coagulation factor II, thrombin receptor-like 2); however, so far, only the second gene has been implicated in striated muscle tissue development( 44 , 45 ), which means that F2r may link HMB and Mapk14 (Fig. 3 and 5).

Another gene of particular importance to the ‘muscle organ development’ term is Myf5, belonging to the MRF family of transcription regulators( 46 ). The high expression of Myf5 in adult skeletal muscle features committed SC and decreases when differentiation to myotubes occurs( 46 , 47 ). Accordingly, decreased expression levels of Myf5 in ESC at the beginning of differentiation may indicate that HMB enhanced withdrawal of equine myoblasts from the cell cycle, compared with control cells. This finding is accompanied by previous reports presenting an HMB-dependent increase in mRNA and protein levels of muscle differentiation markers such as MyoD and myogenin( 8 , 16 ). However, at the time of our analysis, none of the differentiation markers reached significance criteria in ESC, which may emphasise the need for time-course studies in the future. Another down-regulated gene in HMB-treated cells was Tgf-β2. Activity of Tgf-β2 has been recently linked with increased proliferation and delayed differentiation in C2C12( 48 ); thus, its down-regulation may confirm HMB-mediated enhancement of differentiation in ESC.

Other ‘muscle organ development’ annotated genes such as Dmd (dystrophin), Lama2 and Lama5 (laminins) encode protein complexes located in muscle sarcolemma and the basal lamina, respectively, protecting sarcolemma from mechanical damage during muscle contraction( 49 , 50 ) and, as described above, contribute to SC anchor in their niche( 31 ). This could be linked to HMB’s ability to decrease post-exercise muscle cell damage in vivo ( 13 , 14 ); however, in cultured ESC, its expression was decreased. The remaining genes annotated to the ‘muscle organ development’ term by DAVID include the following: Zfp91 (zinc finger protein 91 homolog), acting as an activator of the non-canonical NF-κB pathway( 33 ); Itgb1bp2 (integrin β-1-binding protein 2, melusin 2)( 33 ); Svil (supervilin), involved in myosin II assembly, cell migration and focal adhesions( 33 ); Murc (muscle-related coiled-coil protein) controlling myofibrillar organisation( 33 ); and Tagln3 (actin cross-linking/gelling protein) involved in contractile properties and early cell differentiation( 33 ).

Muscle protein metabolism

One of the first described mechanisms of HMB action was the effect on muscle protein metabolism. Preliminary studies suggest that HMB protects the skeletal muscle by inhibiting protein degradation( 5 ) and by stimulating protein synthesis( 6 ); however, this issue is subjected to constant research( 17 ). Functional analyses have demonstrated significant DEG enrichment of terms associated with cellular protein maintenance (Table 3, Fig. 4). The three most important genes of this group are Cul3 (cullin 3), Trim63 and Mapk14 (Fig. 5). Cul3 is a scaffold protein of E3 ubiquitin-protein ligase complexes, which mediate the ubiquitination and subsequent proteasomal degradation of target proteins. Cul3 also interacts with Kelch family proteins, and disturbances in functioning of this complex are implicated in muscle myopathies( 51 ). E3 Ubiquitin ligase produced by Trim63 regulates the proteasomal degradation of muscle proteins and inhibits de novo skeletal muscle protein synthesis under amino acid starvation, consequently leading to muscle atrophy( 52 ). As observed in the present study, down-expression of Trim63 mediated by HMB confirms the results obtained by Aversa et al.( 39 ) in a dexamethasone-induced muscle atrophy model; however, in two most recent studies, the authors failed to demonstrate a similar effect on Trim63 expression upon fasting in human and pig muscles( 17 , 53 ). This indicates that the effect of HMB on this gene expression could be species and/or condition related. Multiple studies suggest that Mapk14 signalling may be involved in HMB-mediated stimulation of protein synthesis in catabolic conditions( 8 , 39 , 54 ), which may be confirmed by the up-regulation of this gene in HMB-treated ESC.

Lipid metabolism and energy homoeostasis

Recent studies have revealed that HMB supplementation may alter metabolism, as evidenced by improved aerobic performance and increased fat loss during exercise( 11 , 12 ). This is confirmed in our study, which showed influence of DEG on cell processes such as ‘energy homoeostasis’, ‘lipid metabolism’, ‘glucose import’, ‘fatty acid oxidation’ and ‘gluconeogenesis’ (Fig. 4 and 5). An extensive amount of research describing the positive role of Mapk14 on glucose uptake( 55 ) and gluconeogenesis( 56 ) has been published. Thereby, we postulate that apart from the established role of Mapk14 in HMB-dependent influence on protein metabolism and cell growth it can mediate HMB influence on energy homoeostasis as well. The rate of post-exercise muscle glycogen synthesis is 2–3-fold slower in horses compared with other mammals( 1 ); therefore, the positive impact of HMB on glucose uptake could enhance this process in equine skeletal muscles. This is an interesting aspect of our study, which deserves more attention in future investigations. Another salient point of HMB influence on metabolism may be the transcription factor Esrra (oestrogen-related receptor α), controlling vast gene networks involved in all aspects of energy homoeostasis, including lipid and glucose metabolism as well as mitochondrial biogenesis and function( 57 ). Common targets algorithm showed its strong association with ‘fatty acid oxidation’ and ‘lipid metabolism’ (Fig. 5). Essra is targeted by Ppargc1b (peroxisome proliferator-activated receptor γ, coactivator 1 β) (PPAR-γ coactivator), a well-established regulator of β-oxidation of fatty acids and oxidative phosphorylation in mitochondria, which is highly induced during myogenic differentiation( 58 ). Prkab2 (protein kinase, AMP-activated, β2 non-catalytic subunit) is essential for the regulation of a multitude of metabolic processes maintaining energy homoeostasis, especially in tissues with high metabolic rates, such as skeletal muscle( 59 ). Bruckbauer et al.( 12 ) reported that HMB increases the activity of Prkab2 in adipocytes and muscle cells; however, our results showed that HMB slightly decreased its expression in ESC at the time of the analysis. Prkab2 senses cellular energy levels. In response to low cellular ATP levels, Prkab2 switches off ATP-consuming anabolic pathways (mechanistic target of rapamycin (mTOR) kinase pathway), which results in inhibition of cell growth, proliferation and macromolecules synthesis, and at the same time Prkab2 switches on catabolic pathways that generate ATP (e.g. glucose uptake, glycolysis, fatty acid oxidation)( 59 ).

In regulation of the cellular process ‘lipid metabolism’, two genes appear to take the lead – Abca1 (ATP-binding cassette, sub-family A, member 1), encoding a membrane-associated protein belonging to the ATP-binding cassette transporters superfamily and Abhd5 (abhydrolase domain-containing protein 5). The analysis indicated up-regulation of both in ESC. The latter encodes a co-activator of adipose triglyceride lipase, thereby enhancing adipocyte and muscle lipolysis( 60 ). Abca1 is a key regulator of the reverse cholesterol transport process and HDL biogenesis. Increased Abca1 expression was demonstrated in skeletal and cardiac muscles in response to training( 61 ), which indicates the role of Abca1 in the reduction of CVD risk by physical exercise.

Several reports have established HMB’s role in supporting muscle cell membrane integrity during exercise( 13 , 14 ). However, as already mentioned, our analysis showed that at least at mRNA levels HMB decreased the expressions of genes encoding sarcolemmal scaffold proteins (Dmd, Lama2, Lama5). Alternatively, functional analysis enrichment of terms associated with lipid maintenance, as well as KEGG pathways ‘biosynthesis of unsaturated fatty acids’ and ‘glicosphingolipids biosynthesis’, may indicate HMB’s ability to support cell membrane integrity by decreasing its rigidity( 62 ). Moreover, this may have an indirect impact on the inflammatory processes, signal transduction and myoblast differentiation( 62 , 63 ) (Fig. 3).

Conclusions

The results presented in this study suggest the capability of HMB to influence ESC proliferation, differentiation and apoptosis as well as inflammatory response, protein anabolism, sarcolemma integrity, and cell energy utilisation and storage. As we have summarised in Fig. 5, most of the above-mentioned processes could be controlled by the Mapk14 gene, which suggests that at least at the mRNA level HMB triggers its cellular responses by stress signalling pathways. It should be noted that in vivo response of ESC to HMB may differ from the presented results because of the heterogeneity of the SC population and undefined postprandial HMB concentrations in equine skeletal muscle. Moreover, transcription is only one step in the regulatory pathway that leads to functional protein synthesis, therefore, further research on the proteomic, biochemical and pharmacodynamic level is highly recommended.

In conclusion, this study demonstrated for the first time that HMB has the potential to influence ESC by controlling its global gene expression. Transcriptomic profile analysis identified valuable gene targets of HMB in ESC, which may support the role of HMB in improving skeletal muscle growth and regeneration in horses; however, the overall role of HMB in equine skeletal muscle remains equivocal and requires further research.

Acknowledgements

The authors gratefully acknowledge Richard Nicholson for his assistance in the writing of this manuscript.

This research was funded by National Science Centre (Poland), grant no. 2011/03/B/NZ5/05697. Publication of this manuscript was supported by KNOW (Leading National Research Centre) Scientific Consortium ‘Healthy Animal – Safe Food’, a decision of the Ministry of Science and Higher Education, no. 05-1/KNOW2/2015.

K. A. S. carried out muscle sampling, RT-qPCR validation of microarray results, ontological analysis, interpretation of the obtained data and wrote the manuscript. A. C. carried out equine satellite cell isolation and culture analysis, RNA isolation and microarray analysis. P. O. participated in the study design and helped in manuscript revision. T. S. participated in the study design, supervised the project, performed muscle sampling and statistical analysis of microarray and RT-qPCR data, as well as assisted in the manuscript revision. All the authors read and approved the final manuscript.

The authors declare that they have no conflicts of interest.

Supplementary material

For supplementary material accompanying this paper visit http://dx.doi.org/10.1017/S000711451600324X.

S000711451600324Xsup.zip (4.1MB, zip)

click here to view supplementary material

References

  • 1. Waller AP & Lindinger MI (2010) Nutritional aspects of post exercise skeletal muscle glycogen synthesis in horses: a comparative review. Equine Vet J 42, 274–281. [DOI] [PubMed] [Google Scholar]
  • 2. Harris PA & Harris RC (2005) Ergogenic potential of nutritional strategies and substances in the horse. Livest Prod Sci 92, 147–165. [Google Scholar]
  • 3. Wilson JM, Fitschen PJ, Campbell B, et al. (2013) International Society of Sports Nutrition Position Stand: beta-hydroxy-betamethylbutyrate (HMB). J Int Soc Sports Nutr 10, 1–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Szcześniak KA, Ostaszewski P, Fuller JC, et al. (2015) Dietary supplementation of β-hydroxy-β-methylbutyrate in animals – a review. J Anim Physiol Anim Nutr 99, 405–417. [DOI] [PubMed] [Google Scholar]
  • 5. Ostaszewski P, Kostiuk S, Balasinska B, et al. (2000) The leucine metabolite 3-hydroxy-3-methylbutyrate (HMB) modifies protein turnover in muscles of laboratory rats and domestic chickens in vitro . J Anim Physiol Anim Nutr 84, 1–8. [Google Scholar]
  • 6. Smith HJ, Mukerji P & Tisdale MJ (2005) Attenuation of proteasome-induced proteolysis in skeletal muscle by beta-hydroxy-beta-methylbutyrate in cancer-induced muscle loss. Cancer Res 65, 277–283. [PubMed] [Google Scholar]
  • 7. Nissen SL & Abumrad NN (1997) Nutritional role of the leucine metabolite bhydroxy-b-methylbutyrate (HMB). J Nutr Biochem 8, 300–311. [Google Scholar]
  • 8. Kornasio R, Riederer I, Butler-Browne G, et al. (2009) β-Hydroxy-β-methylbutyrate (HMB) stimulates myogenic cell proliferation, differentiation and survival via the MAPK/ERK and PI3K/Akt pathways. Biochim Biophys Acta 1793, 755–763. [DOI] [PubMed] [Google Scholar]
  • 9. Tatara R (2008) Neonatal programming of skeletal development in sheep is mediated by somatotrophic axis function. Exp Physiol 93, 763–772. [DOI] [PubMed] [Google Scholar]
  • 10. Fernyhough ME, Helterline Dl & Vierck Jl (2004) Myogenic satellite cell proliferative and differentiative responses to components of common oral ergogenic supplements. Res Sport Med 12, 161–190. [Google Scholar]
  • 11. Vukovich MD & Dreifort GD (2001) Effect of beta-hydroxy beta-methylbutyrate on the onset of blood lactate accumulation and V(O)(2) peak in endurance-trained cyclists. J Strength Cond Res 15, 491–497. [PubMed] [Google Scholar]
  • 12. Bruckbauer A, Zemel MB, Thorpe T, et al. (2012) Synergistic effects of leucine and resveratrol on insulin sensitivity and fat metabolism in adipocytes and mice. Nutr Metab (Lond) 9, 77. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Ostaszewski P, Kowalska A, Szarska E, et al. (2012) Effects of β-hydroxy-β-methylbutyrate and γ-oryzanol on blood biochemical markers in exercising thoroughbred race horses. J Equine Vet Sci 32, 542–551. [Google Scholar]
  • 14. Miller P, Sandberg L & Fuller JC Jr (1998) The effects of supplemental β-hydroxy-β-methylbutyrate (HMB) on training and racing thoroughbreds. Assoc Equine Sports Med Proc 1, 23–24. [Google Scholar]
  • 15. Mauro A (1961) Satellite cell of skeletal muscle fibers. J Biophys Biochem Cytol 9, 493–495. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Alway SE, Pereira SL, Edens NK, et al. (2013) β-Hydroxy-β-methylbutyrate (HMB) enhances the proliferation of satellite cells in fast muscles of aged rats during recovery from disuse atrophy. Exp Gerontology 48, 973–984. [DOI] [PubMed] [Google Scholar]
  • 17. Kao M, Columbus DA, Suryawan A, et al. (2016) Enteral β-hydroxy-β-methylbutyrate supplementation increases protein synthesis in skeletal muscle of neonatal pigs. Am J Physiol Endocrinol Metab (Epublication ahead of print version 3 May 2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Szcześniak KA, Ciecierska A, Ostaszewski P, et al. (2016) Transcriptomic profile adaptations following exposure of equine satellite cells to nutriactive phytochemical gamma-oryzanol. Genes Nutr 11, 5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Brazma A, Hingamp P, Quackenbush J, et al. (2001) Minimum information about a microarray experiment (MIAME) – toward standards for microarray data. Nat Genet 29, 365–371. [DOI] [PubMed] [Google Scholar]
  • 20. Edgar R, Domrachev M & Lash AE (2002) Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acid Res 30, 207–210. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Livak KJ & Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method. Methods 25, 402–408. [DOI] [PubMed] [Google Scholar]
  • 22. Bustin SA, Benes V, Garson JA, et al. (2009) The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55, 611–622. [DOI] [PubMed] [Google Scholar]
  • 23. Huang DW, Sherman BT & Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4, 44–57. [DOI] [PubMed] [Google Scholar]
  • 24. Asakura A, Komaki M & Rudnicki M (2001) Muscle satellite cells are multipotential stem cells that exhibit myogenic, osteogenic, and adipogenic differentiation. Differentiation 68, 245–253. [DOI] [PubMed] [Google Scholar]
  • 25. Sacco A, Doyonnas R, Kraft P, et al. (2008) Self-renewal and expansion of single transplanted muscle stem cells. Nature 456, 502–506. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Ono Y, Boldrin L, Knopp P, et al. (2010) Muscle satellite cells are a functionally heterogeneous population in both somite-derived and branchiomeric muscles. Dev Biol 337, 29–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Motohashi N & Asakura A (2014) Muscle satellite cell heterogeneity and self-renewal. Front Cell Dev Biol 2, 1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Manzano R, Toivonen JM, Calvo AC, et al. (2011) Sex, fiber-type, and age dependent in vitro proliferation of mouse muscle satellite cells. J Cell Biochem 112, 2825–2836. [DOI] [PubMed] [Google Scholar]
  • 29. Yada E, Yamanouchi K & Nishihara M (2006) Adipogenic potential of satellite cells from distinct skeletal muscle origins in the rat. J Vet Med Sci 68, 479–486. [DOI] [PubMed] [Google Scholar]
  • 30. Essén B, Lindholm A & Thornton J (1980) Histochemical properties of muscle fibre types and enzyme activities in skeletal muscles of Standardbred trotters of different ages. Equine Vet J 12, 175–180. [DOI] [PubMed] [Google Scholar]
  • 31. Bröhl D, Vasyutina E, Czajkowski MT, et al. (2012) Colonization of the satellite cell niche by skeletal muscle progenitor cells depends on Notch signals. Dev Cell 23, 469–481. [DOI] [PubMed] [Google Scholar]
  • 32. Bischoff R (1990) Interaction between satellite cells and skeletal muscle fibers. Development 109, 943–952. [DOI] [PubMed] [Google Scholar]
  • 33. Stelzer G, Dalah I, Stein TI, et al. (2011) In-silico human genomics with GeneCards. Hum Genomics 5, 709. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Jones NC, Tyner KJ, Nibarger L, et al. (2005) The p38α/β MAPK functions as a molecular switch to activate the quiescent satellite cell. J Cell Biol 169, 105–116. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Troy A, Cadwallader AB, Fedorov Y, et al. (2012) Coordination of satellite cell activation and self-renewal by Par-complex-dependent asymmetric activation of p38α/β maPK. Cell Stem Cell 11, 541–553. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Perdiguero E, Ruiz-Bonilla V, Gresh L, et al. (2007) Genetic analysis of p38 MAP kinases in myogenesis: fundamental role of p38α in abrogating myoblast proliferation. EMBO J 26, 1245–1256. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Wang J & Walsh K (1996) Resistance to apoptosis conferred by cdk inhibitors during myocyte differentiation. Science 273, 359–361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Wang Y, Huang S, Sah VP, et al. (1998) Cardiac muscle cell hypertrophy and apoptosis induced by distinct members of the p38 mitogen-activated protein kinase family. J Biol Chem 273, 2161–2168. [DOI] [PubMed] [Google Scholar]
  • 39. Aversa Z, Alamdari N, Castillero E, et al. (2012) β-Hydroxy-β-methylbutyrate (HMB) prevents dexamethasone-induced myotube atrophy. Biochem Biophys Res Commun 423, 739–743. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Kan W, Zhao K, Jiang Y, et al. (2004) Lung, spleen, and kidney are the major places for inducible nitric oxide synthase expression in endotoxic shock: role of p38 mitogen-activated protein kinase in signal transduction of inducible nitric oxide synthase expression. Shock 21, 281–287. [DOI] [PubMed] [Google Scholar]
  • 41. Mitsutaka Y, Sumito O, Hidetaka O, et al. (2015) Beta-hydroxy-beta-methylbutyrate inhibits lipopolysaccharide-induced interleukin-6 expression by increasing protein phosphatase-1α expression. RNA Transcription 1, 1–5. [Google Scholar]
  • 42. Cuenda A & Cohen P (1999) Stress-activated protein kinase-2/p38 and a rapamycin-sensitive pathway are required for c2c12 myogenesis. J Biol Chem 274, 4341–4346. [DOI] [PubMed] [Google Scholar]
  • 43. Han J & Molkentin JD (2000) Regulation of MEF2 by p38 MAPK and its implication in cardiomyocyte biology. Trends Cardiovasc Med 10, 19–22. [DOI] [PubMed] [Google Scholar]
  • 44. Pawlinski R, Tencati M, Hampton CR, et al. (2007) Protease-activated receptor-1 contributes to cardiac remodeling and hypertrophy. Circulation 116, 2298–2306. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Chevessier F, Hantaï D & Verdière-Sahuqué M (2001) Expression of the thrombin receptor (PAR-1) during rat skeletal muscle differentiation. J Cell Physiol 189, 152–161. [DOI] [PubMed] [Google Scholar]
  • 46. Bentzinger CF, Wang YX & Rudnicki MA (2012) Building muscle: molecular regulation of myogenesis. Cold Spring Harb Perspect Biol 4, a008342. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Hansen A (2014) Myostatin mRNA expression in cultured equine satellite cells. Minneapolis, MN: University of Minnesota Digital Conservancy. http://hdl.handle.net/11299/163114; http://conservancy.umn.edu/handle/11299/163114 (accessed March 2016).
  • 48. De Mello F, Streit DP, Sabin N, et al. (2015) Dynamic expression of tgf-β2, tgf-β3 and inhibin βA during muscle growth resumption and satellite cell differentiation in rainbow trout (Oncorhynchus mykiss). Gen Comp Endocrinol 210, 23–29. [DOI] [PubMed] [Google Scholar]
  • 49. García-Pelagio KP, Bloch RJ, Ortega A, et al. (2011) Biomechanics of the sarcolemma and costameres in single skeletal muscle fibers from normal and dystrophin-null mice. J Muscle Res Cell Motil 31, 323–336. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Kuang W, Xu H, Vilquin JT, et al. (1999) Activation of the lama2 gene in muscle regeneration: abortive regeneration in laminin alpha2-deficiency. Lab Invest 79, 1601–1613. [PubMed] [Google Scholar]
  • 51. Gupta VA & Beggs AH (201. 4) Kelch proteins: emerging roles in skeletal muscle development and diseases. Skelet Muscle 4, 11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52. Eddins MJ, Marblestone JG, Kumar KGS, et al. (2011) Targeting the ubiquitin E3 ligase MuRF1 to inhibit muscle atrophy. Cell Biochem Biophys 60, 113–118. [DOI] [PubMed] [Google Scholar]
  • 53. Rittig N, Bach E, Thomsen HH, et al. (2016) Anabolic effects of leucine-rich whey protein, carbohydrate, and soy protein with and without β-hydroxy-β-methylbutyrate (HMB) during fasting-induced catabolism: a human randomized crossover trial. Clin Nutr (epublication ahead of print version 25 May 2016). [DOI] [PubMed] [Google Scholar]
  • 54. Pimentel GD, Rosa JC, Lira FS, et al. (2011) β-Hydroxy-β-methylbutyrate (HMβ) supplementation stimulates skeletal muscle hypertrophy in rats via the mTOR pathway. Nutr Metab (Lond) 8, 11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55. Somwar R, Perreault M, Kapur S, et al. (2000) Activation of p38 mitogen-activated protein kinase alpha and beta by insulin and contraction in rat skeletal muscle: potential role in the stimulation of glucose transport. Diabetes 49, 1794–1800. [DOI] [PubMed] [Google Scholar]
  • 56. Cao W, Collins QF, Becker TC, et al. (2005) p38 Mitogen-activated protein kinase plays a stimulatory role in hepatic gluconeogenesis. J Biol Chem 280, 42731–42737. [DOI] [PubMed] [Google Scholar]
  • 57. Huss JM, Torra IP, Staels B, et al. (2004) Estrogen-related receptor alpha directs peroxisome proliferator-activated receptor alpha signaling in the transcriptional control of energy metabolism in cardiac and skeletal muscle. Mol Cell Biol 24, 9079–9091. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58. Shao D, Liu Y, Liu X, et al. (2010) PGC-1β-regulated mitochondrial biogenesis and function in myotubes is mediated by NRF-1 and ERRα. Mitochondrion 10, 516–527. [DOI] [PubMed] [Google Scholar]
  • 59. Towler MC & Hardie DG (2007) AMP-activated protein kinase in metabolic control and insulin signaling. Circ Res 100, 328–341. [DOI] [PubMed] [Google Scholar]
  • 60. Sanders MA, Madoux F, Mladenovic L, et al. (2015) Endogenous and synthetic ABHD5 ligands regulate ABHD5-perilipin interactions and lipolysis in fat and muscle. Cell Metab 22, 851–860. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61. Ghanbari-Niaki A (2010) Treadmill exercise training enhances ATP-binding cassette protein-A1 (ABCA1) expression in male rats’ heart and gastrocnemius muscles. Int J Endocrinol Metab 8, 206–210. [Google Scholar]
  • 62. Blondelle J, Ohno Y, Gache V, et al. (2015) HACD1, a regulator of membrane composition and fluidity, promotes myoblast fusion and skeletal muscle growth. J Mol Cell Biol 7, 429–440. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63. Cambron LD & Leskawa KC (1994) Glycosphingolipids during skeletal muscle cell differentiation: comparison of normal and fusion-defective myoblasts. Mol Cell Biochem 130, 173–185. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

For supplementary material accompanying this paper visit http://dx.doi.org/10.1017/S000711451600324X.

S000711451600324Xsup.zip (4.1MB, zip)

click here to view supplementary material


Articles from The British Journal of Nutrition are provided here courtesy of Cambridge University Press

RESOURCES