The effect of biologically active vitamin D on differentiating skeletal muscle cells
Abstract
Vitamin D deficiency can cause fat infiltration and this will lead to muscle 'quality' reduction. The probable mechanism of origin of these adipose cells is that abnormal trans-differentiation of myogenic precursor cells into adipocytes lead to the fat form within the intermuscular space. Myogenic precursor cells keep the potential to trans-differentiate towards the adipogenic lineage and VitD has potent effects on both adipogenesis and myogenesis. Therefore, the experiment is designed to investigate the effect of a broad range of concentrations of VitD3 active form (1,25(OH)2D3) on the capacity of the murine C2C12 muscle cell line to trans-differentiate towards the adipogenic lineages. C2C12 cells were cultured in adipogenic media and with increasing 1,25(OH)2D3 concentration (0, 10-13, 10-11, 10-9, 10-7 or 10-5M) for up to 6 days, the expression of muscle and fat gene markers were measured. The results showed that physiological concentration (10-13 and 10-11M) induces adipogenesis and myogenesis, while supraphysiological concentration (10-5M) inhibit both. (150)
Introduction
Nowadays, Vit D deficiency is considered as worldwide problem and influencing upwards of one billion people. Vit D deficiency can cause myopathy and atrophy of skeletal muscle (Holick 2006). Due to fat infiltration, there will be a concomitant reduction in muscle 'quality' (Ryall et al., 2008). The deficiency of Vit D is associated with skeletal muscle and Vit D supplementation can increase fast witch fibers in aged and skeletal muscle by improving overall muscle strength (Harwood et al., 2004). However there is no evidence showing that VitD supplementation has influence on fat infiltration within muscle. The probable mechanism of t origin of these adipose cells is that abnormal trans-differentiation of myogenic precursor cells into adipocytes lead to the fat form within the intermuscular space (Vettor et al., 2009). Myogenic precursor cells keep the potential to trans-differentiate towards the adipogenic lineage and VitD has potent effects on both adipogenesis and myogenesis (Grimaldi et al., 1997, Seale et al., 2008, Kong and Li, 2006 Garcia et al., 2011). However, there is still unknown whether Vit D influences the trans-differentiate of myogenic precursor cells into adipocytes.
The hypothesis is in adipogenic media, calcitriol would cause the muscle cells to differentiate toward an adipogenic cell type. This will be characterized by an increase in the expression of genes associated with white adipocytes. According to this hypothesis, an experiment is designed to investigate the effect of a broad range of concentrations of VitD3 active form (1,25(OH)2D3) on the capacity of the murine C2C12 muscle cell line to trans-differentiate towards the adipogenic lineages.
Methods
In order to examine the effect on calcitriol of skeletal muscle cells, the C2C12 cell line was used. These cells were cultured in DMEM (Sigma) supplemented and maintained at 37˚C and 5% CO2 until 70-80% confluent (day 0). After that, the cells were switched to adipogenic differentiation media and incubated for up to 6 days, also at 37˚C and 5% CO2. Furthermore, this media was added with increasing concentrations (0, 10-13, 10-11, 10-9, 10-7 or 10-5M) of 1,25(OH)2D3 in DMSO. Experiments were carried out in triplicate. After six days, the cells were stained with Oil Red-O to recognize lipid droplets.
At timepoints day 2 and day 6, the total RNA from C2C12 was extracted, 0.5ug of total RNA from each sample was used to synthesize first strand cDNA. The random hexamer primers were used in synthesis to give a final volume of 100ul. This was the stock first strand cDNA sample. In order to make PCR, a total of 15ul sample should be made, which include 10ul Master Mix and 5ul cDNA (Appendix1). These samples should be provided in a 96 well microtitre plate and three replicates of the experiment, Rep A, B and C.
Furthermore, a standard curve is used to quantify the gene expression, which is used to convert Crossing point (Cp) that produced by quantitative PCR machine for each experimental first strand cDNA sample into ‘linear’ values (an “RNA quantity equivalent” value). The relative comparison method, which was used a serial dilution of a pool of all the experimental stock first strand cDNA samples to produce a standard curve, was involved. (Statistics result will be shown in appendix 2)
Results
The tendency that can be observed from figure 1 is that with the concentration of 1,25(OH)2D3 (M) increased, the percentage area of lipid accumulation is decreased (p<0.001). Compared with DMSO control cells, the group of 1,25(OH)2D3 (M) on 10-11 does not have significant effect, while, other groups have significant effect (** p<0.01; *** p<0.001).
For CKM gene, the concentration (10-13 and 10-11 M) of 1,25(OH)2D3 increased the expression, but 10-5 M of 1,25(OH)2D3 suppressed differentiation for CKM and myogenin gene at both day 2 and day 6 (P<0.001 for two gene respectively, 1,25(OH)2D3 concentration*day interactions, figure 2 and 3; table 1and2). The levels of CKM mRNA expression at day 6 was higher than day 2, whereas for MYOG gene, this trend was not clearly (Figure 1 and2).
The expression of two white adipocytes’ gene markers (PPARγ2, figure 3; FABP4, figure 4) were induced in a 1,25(OH)2D3 concentration and time-dependent manner (P<0.001 for two gene respectively, 1,25(OH)2D3 concentration*day interactions, table 3 and 4)
For both these two genes, the low physiological concentration (10-13M) of 1,25(OH)2D3 increased the expression and the expression was inhibited at supraphysiological concentration (10-7,10-5M). Furthermore, the levels of PPARγ2 reached peaking at day 2 and decreased in day 6, while the levels of FABP4 peaked at day 6.
At physiological range (10-11, 10-9M) of 1,25(OH)2D3, the expression of Elovl3 and CIDEA increased and was blocked at supraphysiological concentration (10-5M), but this trend just can be observed at day 6. (P<0.001 for gene Elovl3, P<0.05 for gene CIDEA,1,25(OH)2D3 concentration*day interactions, table 5and6, figure 6 and 7).
Discussion
This dose-dependent experiment illustrates that active form of Vit D (1,25(OH)2D3) has the ability to induce C2C12 muscle cells to differentiate toward an adipogenic cell type. The research of Grimaldi et al. (1997) indicated that exposed C2C12 cells to long-chain fatty acids (LCFA) or thiazolidinediones (TZDs) could convert the differentiation pathway of myoblasts to adipoblasts by inhibiting the formation of multinucleated myotubes and the expression of specific muscle markers, and then this leads in parallel to the expression of a typical adipose differentiation. The reason could be associated with increased expression of adipogenic marker genes—PPARγ2 and FABP4. PPARγ2 can regulate adipocyte differentiation and lipogenic genes during adipogenesis; it is able to convert myoblasts trans-differentiation into adipocytes with a PPARγ-ligand (Yu et al., 2006). In this experiment, expression of PPARγ2 gene reached peak at low concentration (10-13M) of 1,25(OH)2D3 and is inhibited at supraphysiological concentration (10-5M), the same as FABP4. This result precisely coincide with figure 8 B and F that low physiological concentration (10-13M) stimulates lipid droplets accumulation and high concentration (10-5 M) block expression. The experiment of Thomson et al. (2007) also show the similar result that high concentration (10-8 M) of 1,25(OH)2D3 inhibits the adipogenic differentiation of 3T3-L1 cells and low concentration (10-10) stimulates it.
The mechanisms for 1,25(OH)2D3 inhibit expression of PPARγ could be related to that Vit D induced decrease in endogenous PPARγ ligand availability. Similar as other nuclear hormone receptors, VDR and PPARs act as a ligand activated transcription factor, both of them in response to their ligand binding, hetero-dimerize with RXR (with limited amount), and bind VDRE and PPRE DNA sequences in the promoters of target genes, respectively. This competitive relationship is led to that with increased VitD 3, more RXR will combine with it (VD3+VDR), so PPARγ cannot express since lack of RXR (Figure 9) (Kong and Li, 2006; Wood, 2008; Matsuda and Kitagishi, 2013).
Because C2C12 muscle cells can be induced to differentiate toward an adipogenic cell type, so the gene markers of brown adipocytes also are tested in the experiment. The research of Seale et al. (2008) proved that ectopic expression of PRDM16 in C2C12 myoblasts induces their differentiation into brown fat cells. Furthermore, adipocytes derived from PRDM16 expressing myogenic precursors strongly activated the expression of brown fat cell-specific genes (Elovl3 and CIDEA). In this study, the gene markers of brown adipocytes are activated in adipogenic media, they expressed not obviously until day 6.
Although C2C12 myoblasts can be induced to differentiate toward an adipogenic cell type, myotubes formation still can be tested in adipogenic media. Grimaldi et al. (1997) indicated that exposure of C2C12 ceils to TZDs or unsaturated LCFA resulted in an almost complete inhibition of CKM expression. However, in this study, the low concentration (10-13, 10-11M) of 1,25(OH)2D3 can increase the expression of muscle markers, instead of inhibit it and at supraphysiological concentration (10-5M), the expression of muscle markers is blocked. Besides, Garcia et al. (2001) displayed that adding 1,25(OH)2D3 to skeletal muscle cells induced an increased expression of myogenic markers (myogenin). This result is consistent with this experiment.
To conclude, physiological concentration (10-13 and 10-11M) induces adipogenesis and myogenesis, while supraphysiological concentration (10-5 M) inhibit both.
Reference
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Figure 1 The relationship between concentration of 1,25(OH)2D3 (M) and % area of lipid accumulation

Figure 2 Expression of gene A CKM (skeletal muscle cell differentiation) in different concentration 1,25(oH)2 D3(M)

Figure 3 Expression of gene B MYOG (skeletal muscle cell differentiation) in different concentration 1,25(OH)2 D3(M)

Figure 4 Expression of gene C PPARG2 (white adipose cell differentiation) in different concentration 1,25(OH)2 D3(M)

Figure 5 Expression of gene D FABP4 (white adipose cell differentiation) in different concentration 1,25(OH)2 D3(M)

Figure 6 Expression of gene E Elovl3 (brown adipose cell differentiation) in different concentration 1,25(OH)2 D3(M)

Figure 7 Expression of gene F CIDEA (brown adipose cell differentiation) in different concentration 1,25(OH)2 D3(M) A
B
C
D
E
F
A
B
C
D
E
F

Figure 8 Dose-dependent effects of 1,25(OH)2D3 on accumulation of lipid droplets in C2C12 cells cultured in adipogenic (G-L) media. Cells were cultured for 6 days in adipogenic media with vehicle (DMSO control) (A) or increasing concentrations of 1,25(OH)2D3 (10-13 (B), 10-11 (C), 10-9 (D), 10-7 (E) or 10-5M (F)). Figure 9 Schematic depiction of the model of mechanism of VDR and PPARs action.

Table 1 Tests of Between-Subjects Effects of Gene A Dependent Variable: CKM | Source | Type III Sum of Squares | df | Mean Square | F | Sig. | Corrected Model | .906a | 11 | .082 | 20.252 | .000 | Intercept | 1.165 | 1 | 1.165 | 286.398 | .000 | Concentration | .357 | 5 | .071 | 17.533 | .000 | Day | .406 | 1 | .406 | 99.692 | .000 | Concentration * Day | .144 | 5 | .029 | 7.084 | .000 | Error | .244 | 60 | .004 | | | Total | 2.316 | 72 | | | | Corrected Total | 1.151 | 71 | | | | a. R Squared = .788 (Adjusted R Squared = .749) |
Table 2 Tests of Between-Subjects Effects of Gene B Dependent Variable: MYOG | Source | Type III Sum of Squares | df | Mean Square | F | Sig. | Corrected Model | 1.172a | 11 | .107 | 16.505 | .000 | Intercept | 4.140 | 1 | 4.140 | 641.180 | .000 | Concentration | .707 | 5 | .141 | 21.903 | .000 | Day | .058 | 1 | .058 | 8.910 | .004 | Concentration * Day | .408 | 5 | .082 | 12.625 | .000 | Error | .387 | 60 | .006 | | | Total | 5.700 | 72 | | | | Corrected Total | 1.560 | 71 | | | | a. R Squared = .752 (Adjusted R Squared = .706) |
Table 3 Tests of Between-Subjects Effects of Gene C Dependent Variable: PPARγ2 | Source | Type III Sum of Squares | df | Mean Square | F | Sig. | Corrected Model | 97.747a | 11 | 8.886 | 86.994 | .000 | Intercept | 36.645 | 1 | 36.645 | 358.747 | .000 | Concentration | 42.772 | 5 | 8.554 | 83.747 | .000 | Day | 24.802 | 1 | 24.802 | 242.807 | .000 | Concentration * Day | 30.173 | 5 | 6.035 | 59.078 | .000 | Error | 6.129 | 60 | .102 | | | Total | 140.521 | 72 | | | | Corrected Total | 103.876 | 71 | | | | a. R Squared = .941 (Adjusted R Squared = .930) |
Table 4 Tests of Between-Subjects Effects of Gene D Dependent Variable: FABP4 | Source | Type III Sum of Squares | df | Mean Square | F | Sig. | Corrected Model | .945a | 11 | .086 | 20.140 | .000 | Intercept | 1.209 | 1 | 1.209 | 283.404 | .000 | Concentration | .587 | 5 | .117 | 27.533 | .000 | Day | .229 | 1 | .229 | 53.581 | .000 | Concentration * Day | .129 | 5 | .026 | 6.058 | .000 | Error | .256 | 60 | .004 | | | Total | 2.410 | 72 | | | | Corrected Total | 1.201 | 71 | | | | a. R Squared = .787 (Adjusted R Squared = .748) |
Table 5 Tests of Between-Subjects Effects of Gene E Dependent Variable: Elovl3 | Source | Type III Sum of Squares | df | Mean Square | F | Sig. | Corrected Model | 35.713a | 11 | 3.247 | 13.994 | .000 | Intercept | 24.078 | 1 | 24.078 | 103.785 | .000 | Concentration | 10.371 | 5 | 2.074 | 8.941 | .000 | Day | 15.402 | 1 | 15.402 | 66.390 | .000 | Concentration * Day | 9.492 | 5 | 1.898 | 8.182 | .000 | Error | 13.456 | 58 | .232 | | | Total | 74.093 | 70 | | | | Corrected Total | 49.169 | 69 | | | | a. R Squared = .726 (Adjusted R Squared = .674) |

Table 6 Tests of Between-Subjects Effects of Gene F Dependent Variable: CIDEA | Source | Type III Sum of Squares | df | Mean Square | F | Sig. | Corrected Model | 43.065a | 11 | 3.915 | 7.666 | .000 | Intercept | 22.879 | 1 | 22.879 | 44.803 | .000 | Concentration | 7.535 | 5 | 1.507 | 2.951 | .021 | Day | 21.814 | 1 | 21.814 | 42.716 | .000 | Concentration * Day | 7.435 | 5 | 1.487 | 2.912 | .022 | Error | 25.023 | 49 | .511 | | | Total | 100.097 | 61 | | | | Corrected Total | 68.088 | 60 | | | | a. R Squared = .632 (Adjusted R Squared = .550) | Appendix 1 Table 1. Quantitative PCR primers Primer Pair | Gene | Primer orientation | Primer sequence (5’ to 3’) | A | CKM | Forward | GCACTGGCCGCAGCAT | | | Reverse | GAGGGTAGTACTTGCCCTTGAACTC | B | MYOG | Forward | CCCATGGTGCCCAGTGAA | | | Reverse | GCAGATTGTGGGCGTCTGTA | C | PPARG2 | Forward | GCATGGTGCCTTCGCTGA | | | Reverse | TGGCATCTCTGTGTCAACCATG | D | FABP4 | Forward | AAGTGGGAGTGGGCTTTGC | | | Reverse | TGGTGACCAAATCCCCATTT | E | Elovl3 | Forward | ATGAATTTCTCACGCGGGTTA | | | Reverse | GCTTACCCAGTACTCCTCCAAAAA | F | CIDEA | Forward | CCAGAGTCACCTTCGACCTATACA | | | Reverse | CTCGTACATCGTGGCTTTGACA |
Primer pairs A and B are for assessing the expression of genes associated with skeletal muscle differentiation
Primer pairs C and D are for assessing the expression of genes associated with white adipose cell differentiation
Primer pairs E and F are for assessing the expression of genes associated with brown adipose cell differentiation

Table 2 For PCR each reaction in a total of 15ul the following constituents are required | Voulme | final conc | SYBR Master solution* (2x) | 7.5ul | x1 | Forward primer (10 uM) | 0.45ul | 0.3 mM | Reverse primer (10 uM) | 0.45ul | 0.3 mM | Water (molecular grade) | 1.6ul | |
10ul total volume. To this 10ul Master Mix is add 5ul cDNA per well
Appendix 2
Table 3. Serial dilution of pooled stock first strand cDNA solution Standard | A | B | C | D | E | F | G | H | concentration relative to 1x stock | 1 | 0.5 | 0.25 | 0.125 | 0.0625 | 0.03125 | 0.015625 | 0.0078125 | Ratio of 1x stock to water (stock:water) | 1:0 | 1:1 | 1:3 | 1:7 | 1:15 | 1:31 | 1:63 | 1:127 | Efficiency = 96.46%
Efficiency = 96.46%

Figure 1 Standard curve of gene A Efficiency = 75.98%
Efficiency = 75.98%

Figure 2 Standard curve of gene B Efficiency = 173.28%
Efficiency = 173.28%

Figure 3 Standard curve of gene C Efficiency = 54.93%
Efficiency = 54.93%

Figure 4 Standard curve of gene D Efficiency = 102.48%
Efficiency = 102.48%

Figure 5 Standard curve of gene E Efficiency = 100.15%
Efficiency = 100.15%

Figure 6 Standard curve of gene F In this experiment, each gene has two groups to test (except gene F), so there are eleven groups’ data for six kinds of gene. In order to choose high accuracy data, the following parameters must be evaluated. • Linear standard curve (R2 > 0.980) • High amplification efficiency (90–105%) Amplification efficiency, E, is calculated from the slope of the standard curve using the following formula: E = 10–1/slope, % Efficiency = (E – 1) x 100%.