Differential global gene expression in red and white skeletal muscle

W. G. Campbell1,2, S. E. Gordon1,2, C. J. Carlson1,2, J. S. Pattison2, M. T. Hamilton1,2, and F. W. Booth1,2

1 Department of Integrative Biology, University of Texas Medical School, Houston, Texas 77030; and 2 Departments of Veterinary Biomedical Sciences and Physiology and Dalton Cardiovascular Center, College of Veterinary Medicine, University of Missouri, Columbia, Missouri 65211


    ABSTRACT
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

The differences in gene expression among the fiber types of skeletal muscle have long fascinated scientists, but for the most part, previous experiments have only reported differences of one or two genes at a time. The evolving technology of global mRNA expression analysis was employed to determine the potential differential expression of ~3,000 mRNAs between the white quad (white muscle) and the red soleus muscle (mixed red muscle) of female ICR mice (30-35 g). Microarray analysis identified 49 mRNA sequences that were differentially expressed between white and mixed red skeletal muscle, including newly identified differential expressions between muscle types. For example, the current findings increase the number of known, differentially expressed mRNAs for transcription factors/coregulators by nine and signaling proteins by three. The expanding knowledge of the diversity of mRNA expression between white and mixed red muscle suggests that there could be quite a complex regulation of phenotype between muscles of different fiber types.

messenger ribonucleic acid; differential expression


    INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

THE MAIN FUNCTION OF SKELETAL MUSCLE is postural support and movement (1, 22), but it also has a major role as a metabolic organ with consequent implications for health. Skeletal muscle is composed of heterogeneous fiber types that vary in contraction velocity, endurance capability, and metabolic enzyme profile. Red muscles have a higher percentage of capillaries, myoglobin, and mitochondria, making them a better aerobic machine than the paler-appearing white muscle (for review, see Ref. 26). Thus red muscle with type I fibers is better suited for long-duration activities, such as postural maintenance. In contrast, white muscle is suited to a "fight or flight" role, having a contractile apparatus tailored for higher velocity contractions and requiring anaerobic glycolytic metabolism to support the high transient energy demand.

The metabolic profile of red vs. white muscle may be protective against the development and progression of chronic disease. Individuals with a higher percentage of red fibers are less likely to have chronic metabolic syndromes, such as insulin resistance (11, 14, 18, 19, 31), glucose intolerance (31), type 2 diabetes (25), obesity (10, 11, 17-19, 28, 33), and a blood lipid profile associated with an increased risk of cardiovascular disease (low high-density lipoprotein, low apolipoprotein A-I, and high triglycerides) (30). Thus the ability of skeletal muscle to oxidize substrates likely plays some role in chronic metabolic diseases.

The ability to study gene expression differences with oligonucleotide arrays may enable researchers to determine those genes responsible for the diversity of muscle fiber composition. Thus the goal of this study was to use the unbiased oligonucleotide array technology to develop a global gene expression profile associated with white vs. mixed red fiber types in ICR mice to gain a better understanding of the gene regulation that underlies the difference between muscle fiber types. The ICR strain was chosen because we have shown that the white portion of the mouse quadriceps muscle group (white muscle/white quad) is comprised of 100% type IIb muscle fibers, whereas the predominantly red soleus is comprised of 70% type I and 30% type IIa fibers (5). For the purpose of this presentation, the mouse soleus muscle is called mixed red due to its mixture of slow oxidative and fast oxidative fibers. It was anticipated that the use of oligonucleotide array technology would reveal mRNAs that are differentially expressed between white and mixed red skeletal muscle and may, therefore, account for the association of fiber type with chronic diseases.


    MATERIALS AND METHODS
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

Animals. Female ICR mice (Harlan Sprague Dawley, Indianapolis, IN) were housed in a temperature- (21°C) and light-controlled environment (12:12-h light-dark cycle) and were provided food and water ad libitum. The experimental protocol was approved by the University of Texas Health Science Center at Houston and University of Missouri Animal Welfare Committees. Before taking muscle samples, mice were anesthetized by an intraperitoneal injection of a 0.10-ml cocktail of ketamine (49 mg/ml), xylazine (6.2 mg/ml), and acepromazine (2.0 mg/ml). Soleus and quadriceps muscles were dissected, and the quadriceps muscle group was further dissected to obtain the white quad. An initial comparison was made using Affymetrix Mu6500 GeneChips (Santa Clara, CA). For this comparison (pool 1), the white quad obtained from different mice (34.0 ± 0.7 g body wt) were pooled for the white muscle sample, while the soleus muscles from 20 mice (33.2 ± 0.6 g body wt; means ± SE, not significantly different from the white muscle group) were pooled to make the mixed red muscle sample (Fig. 1). Further comparisons involving two independent samples of the white quad and soleus muscles were made using the newer Affymetrix Mu11K SubB GeneChips. Each of these samples was comprised of muscle tissue pooled from mice before RNA isolation. Pool WQ2 consisted of the white quad, whereas pool SO2 was composed of soleus muscles (Fig. 1); both pools were formed from the same five mice (body wt 30.9 ± 0.9 g, white quad pair wt 98.1 ± 3.3 mg, and soleus pair wt 13.3 ± 0.7 mg). Pool WQ3 and pool SO3 were formed from another five mice (body wt 30.1 ± 1.2 g, white quad pair wt 102.1 ± 7.3 mg, and soleus pair wt 13.1 ± 0.7 mg; all weights not significantly different from their respective samples in pool 2).


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Fig. 1.   cRNA from 3 independent samples of soleus (SO) and white quad (WQ) muscles were applied to microarrays in the following manner. Pool SO1 represents 20 pairs of SO muscles, and pool WQ1 represents 7 pairs of WQ muscles (from the animals used for the SO pool), applied to Affymetrix Mu6500 microarrays. Pool SO2 represents 5 pairs of SO muscles, whereas pool WQ2 represents 5 pairs of WQ muscles from the same animals. Pools SO3 and WQ3 each represent 5 pairs of muscles from the same animals and are from different animals than SO2 and WQ2. The pools were hybridized to Affymetrix microarrays. Fold changes compare mRNA quantity in red muscle (soleus) to mRNA quantity in white muscle (white quad), which was normalized to 100%. Positive-fold changes indicate mRNA quantities that are higher in red muscle than white muscle; negative-fold changes indicate mRNA quantities that are lower in red muscle than white muscle.

RNA processing. Muscles were homogenized on ice in TRIzol (GIBCO BRL, Gaithersburg, MD) by Polytron (Kinematica, Lucerne, Switzerland) at a setting of seven for three pulses of 15 s each. Cellular debris was removed by centrifugation for 5 min at 12,000 g, and total RNA was isolated using the TRIzol protocol (GIBCO BRL). For RNA samples assayed using Mu6500 arrays, poly(A)+ RNA selection was carried out using Oligotex (Qiagen, Santa Clara, CA). Isolation of poly(A)+ RNA in processing RNA for microarray experiments is optional and was omitted for samples assayed using Mu11K SubB arrays. First- and second-strand synthesis was carried out using SuperScript Choice (GIBCO BRL), in vitro transcription to incorporate biotinylated nucleotides by BioArray High Yield (Enzo Diagnostics, Farmingdale, NY), and final purification with RNeasy (Qiagen).

Microarray analysis. Hybridization, scanning, and preliminary analysis of Mu6500 samples were carried out by Research Genetics (Huntsville, AL). Hybridization and scanning of Mu11K SubB samples were carried out by the authors in the laboratory of Dr. Eric P. Hoffman at Children's Hospital (Washington, DC). Expression of each gene on the microarray was quantified by ~20 perfect match probe sequences corresponding to different 25-mer regions within the gene. Specific hybridization of each probe was tested by the inclusion of ~20 corresponding probes containing a single base mismatch at the middle position of each 25-mer oligonucleotide. The perfect match and mismatch probes corresponding to one gene is designated a probe set. Thus there were ~20 distinct specific hybridization events for each gene analyzed.

Of the 6,320 sequences represented on the Affymetrix Mu6500 set of GeneChips, there are probe sets designed to measure the expression of 3,282 genes and 3,038 expressed sequence tags (ESTs). There are also positive and negative control probe sets on each chip for bacterial sequences. Biotinylated transcripts for these bacterial sequences were in vitro transcribed in a separate reaction from the muscle sample cRNAs and spiked into the muscle samples before hybridization to validate the hybridization step in the event of poor quality experimental cRNA samples. Utilizing metrics and parameters previously designed (20, 21), GeneChip Expression Analysis Suite version 3.2 (Affymetrix) was used to determine which mRNAs were detected in white and mixed red muscle samples and which mRNAs were expressed at different levels between the two samples on the Mu6500 microarrays (Fig. 1). Control and experimental samples were normalized to each other by calculating the mean intensity for each sample after excluding the genes within a sample having the highest 2% and lowest 2% of intensities. Values within each sample were then adjusted by a factor such that the renormalized mean intensity was equal for all samples.

Of the 6,519 sequences represented on the Affymetrix Mu11K SubB GeneChips, there are probe sets designed to determine the expression of 2,790 genes and 3,279 ESTs. Procedures for samples hybridized to Mu11K SubB chips were identical to the Mu6500 chips, except that Eukaryotic Hybridization Control Kit (Affymetrix) was used for controls, preliminary analysis was carried out using version 3.3 of the GeneChip Expression Analysis Suite (Affymetrix), and microarrays were now scanned twice [before antibody amplification (scan 1) and after antibody amplification (scan 2)]. The specified muscles from five mice were pooled to form a single observation. Further details on experimental groups, replications, and comparisons are shown in Fig. 1.

The algorithm for determining differentially expressed genes with oligonucleotide microarrays is optimized to minimize false positives (20, 21), plus the thresholds for our selection criteria were set conservatively to further minimize false positives. Thus it is likely that few genes were incorrectly classified as increasing or decreasing between muscle fiber types. These stringent selection criteria may prevent detection of some differentially expressed genes, resulting in potential false negatives. Thus some underestimation of the number of the actual differentially expressed genes likely exists.

The Affymetrix analysis software (Microarray Suite 4.0) contains algorithms for determining the relative presence or absence of a given mRNA in the sample. One matrix from this analysis is called an absolute call, which provides calls of present, marginal, or absent. Affymetrix software also calculates a difference call from a second matrix, which identifies the differences between two compared samples for a given mRNA. The output of this difference call matrix can be increased, marginally increased, decreased, marginally decreased, and no change compared with the designated baseline sample. Using Affymetrix software, the following multiple thresholds had to be surpassed for mRNAs to be declared as differentially expressed between soleus and white quad on an antibody-amplified scan with the Mu11K SubB microarray: 1) a specific mRNA had to be declared "present" from each absolute call in all three observations of a particular fiber type, e.g., SO2A, SO2B, and SO3; 2) a minimum of seven similar difference calls, i.e., seven increases or seven decreases between the soleus and white quad had to occur in the nine comparison calls (3 white quad × 3 soleus); 3) if more than 4 of the 20 perfectly matched probe pairs for each mRNA in the antibody-amplified stain exceeded maximum detection limits of the scanner, then steps 1-3 were repeated on the preantibody scan of the same mRNA; and 4) 10 or more of the 20 probe pairs were required to be read positive for each mRNA (i.e., where positive means that the intensity of the perfect probe is greater than the intensity of the mismatched probe). Finally, only mRNAs that were differentially expressed between fiber types on both the Mu6500 and Mu11K SubB microarrays were included in Table 1.

                              
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Table 1.   Differential mRNA expression between red and white skeletal muscle

Affymetrix software also calculates a fold change for each comparison, which is an estimate of the differences in intensities (determined by the quantity of mRNAs hybridized to the probes on the chips) between the baseline and experimental samples. For mRNAs differentially expressed between fiber types on the Mu11K SubB microarrays, fold changes were calculated by applying the following (see Fig. 1)


<IT>x</IT><IT>=</IT><FR><NU><AR><R><C><FENCE><FR><NU>(SO3 v WQ3A)<IT>+</IT>(SO3 v WQ3B)</NU><DE><IT>2</IT></DE></FR></FENCE><IT>+</IT><FENCE><FR><NU>(SO2A v WQ2)<IT>+</IT>(SO2B v WQ2)</NU><DE><IT>2</IT></DE></FR></FENCE></C></R><R><C><IT> +</IT><FENCE><FR><NU>(SO2A v WQ3A)<IT>+</IT>(SO2A v WQ3B)<IT>+</IT>(SO2B v WQ3A)<IT>+</IT>(SO2B v WQ3B)</NU><DE><IT>4</IT></DE></FR></FENCE><IT>+</IT><FENCE><FR><NU>(SO3 v WQ2)</NU><DE><IT>1</IT></DE></FR></FENCE></C></R></AR></NU><DE><IT>4</IT></DE></FR>

<IT>y</IT><IT>=</IT>(SO1 v WQ1)

FC<IT>=</IT><FR><NU>(<IT>2x</IT>)<IT>+</IT>(<IT>y</IT>)</NU><DE><IT>3</IT></DE></FR>

where x = fold change for Mu11K SubB (n = 2 pools); v stands for vs.; y = fold change for Mu6500 (n = 1 pool); and FC = the composite fold changes for both the Mu6500 and Mu11K SubB microarrays reported in Table 1 for each mRNA.

We used an Affymetrix-recommended method for deducing the chip-to-chip reproducibility by calculating the number of false calls. Note that when comparing an identical pool of mRNAs placed on two different chips, ideally, one would expect every gene to be called (difference call) the same, yielding no increases or decreases. When genes are not called the same, they are called false calls. The number of false calls is the sum of the number of false increases and false decreases. False increases are calculated by dividing the number of mRNAs called present with at least twofold increases by the total number of present calls. False decreases are determined by dividing the number of mRNAs when present in the baseline sample with at least twofold decreases by the total number of the mRNAs designated as present in the baseline sample absolute calls. These calculations yielded <1% false calls for the identical white quad (WQ3A vs. WQ3B) samples compared and 7% for identical soleus (SO2A vs. SO2B) samples.


    RESULTS
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

Of the 6,519 gene and EST sequences analyzed by the Mu11K SubB microarray, 1,548 (24%) were detected in mouse white quad, and 1,317 (20%) were detected in soleus muscle. Among these, 177 (~3% of genes and ESTs on the microarray, and ~11-13% of genes and ESTs that were expressed in white or mixed red skeletal muscle) were observed to have different expression levels between the two muscle types. If this proportionality holds (177 differences on a microarray with 6,519 genes and ESTs), and the mouse is eventually found to have 80,000 genes, then our results would predict that there could be 2,200 differences in mRNA expression between white and mixed red muscle types. Because whole muscle was the source of cRNA for this study, a variety of cell types may contribute to these differentials in gene expression, including skeletal muscle cells, smooth muscle cells, satellite cells, endothelial cells, nerve, and fibroblasts.

Each differentially expressed mRNA reported in Table 1 is based on three independent muscle samples for each fiber type showing a differential call in the same direction (see MATERIALS AND METHODS and Fig. 1). Due to the lack of functional information for EST sequences, ESTs are not categorized as to function and are not reported in Table 1. The complete list of genes and ESTs differentially expressed between muscle types can be accessed at http://efbioinfo.biosci.missouri.edu/BoothWeb/red-white.html.


    DISCUSSION
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

A goal of this study was to discover if additional mRNAs could be found whose expression shows preference to a specific fiber type. This would advance our knowledge of the gene expression profile that might give rise to the contractile and metabolic differences between fiber types. Microarray analysis confirmed a previous observation (27) of the muscle type differential expression of the mRNA encoding the muscle LIM protein transcription factor. An additional nine mRNAs representing transcription factors that were not previously known to be expressed in a fiber type manner were identified as differentially expressed by microarray analysis. This is intriguing because the newly identified factors/coregulators may be candidates for transcriptional regulation of the specificity of the metabolic and contractile characteristics of fiber types.

Although the fold change in differential expression determined by Northern analysis and microarray technology has not always been the same (15), the direction of change should, in every case, be the same. Comparison of the results of the current microarray experiment (Table 1) with previously reported differential fiber type-specific mRNA expression obtained by Northern analysis indicated agreement. The previously reported fiber type differences used for comparison included cardiac/slow myosin light chain 2 (9), fatty acid transport protein (CD36) (4), medium chain acyl-CoA dehydrogenase (6), muscle LIM protein (27), myoglobin (32), myosin heavy chain IIb (7), Na+-K+-ATPase beta 1-subunit (13), and parvalbumin (3). Furthermore, all differentially expressed genes of the citric acid cycle, oxidative phosphorylation, lipid metabolism, and contractile protein isoforms were more highly expressed according to the fiber type predominance previously reported for enzymatic or protein determinations. Thus for those mRNAs in Table 1, microarray analysis as performed here was able to confirm previously reported differences in gene expression between fiber types.

Our observations show that the mRNAs for two LIM proteins in mixed red muscle were 86-fold and 9-fold that of white quad, which confirms and extends on the findings of Schneider et al. (27) by identifying a LIM protein 1 (SLIM1) mRNA as a second LIM protein that is differentially expressed. Proteins that contain LIM domains have been discovered to play important roles in a variety of fundamental biological processes, including development of cell types, organ development, transcriptional regulation, and cytoskeletal organization (2). Further experiments are required to clarify a potential role.

CCAAT enhancer binding protein (C/EBP)-delta mRNA was found to be 36-fold lower in the mouse mixed red soleus than white quad. Transgenic mice lacking C/EBP-beta and C/EBP-delta have impaired adipogenesis (29). The promoter for human CD36 contains a potential C/EBP-beta and C/EBP-delta binding site, but it is not known if this site is active. If so, it may be an inhibitor of CD36 transcription based on their inverse expressions. C/EBP-delta has been shown to be induced by insulin in adipocytes (23). Mixed red muscle has more insulin sensitivity (16), higher triglyceride stores (8), and greater maximal palmitate uptake (4) and CD36 mRNA, but a 36-fold lower C/EBP-delta mRNA than white muscle. Based on this evidence, a hypothesis may be formulated that the C/EBP-delta is a candidate for a transcription factor that could play some role in controlling the metabolic differences between skeletal muscle fiber types.

The different metabolic capacities of white and mixed red skeletal muscle are well known. Not surprisingly, 14 of the 49 (29%) differentially expressed genes identified in this study could be categorized as energy metabolism genes. Three genes with functions in fatty acid metabolism [CD36 (fatty acid transport protein), medium chain acyl-CoA dehydrogenase (fatty acid oxidation), and peroxisome proliferator-activated receptor (PPAR)-alpha (regulates the expression of several key genes in fatty oxidation)] may play a role in the association of mixed red muscle fiber type with a favorable blood lipid profile. Horowitz et al. (12) recently reported that endurance training increased skeletal muscle PPAR-alpha protein in humans. They speculated that regular exposure to elevated plasma glucocorticoids, such as cortisol, together with a high rate of fatty acid flux during endurance training, may increase PPAR-alpha mRNA expression, which was not determined in that study. Our data of a 3.5-fold higher level of PPAR-alpha mRNA in mixed red than white muscle would suggest that plasma glucocorticoid concentrations are not solely responsible for PPAR-alpha expression in the resting state.

Ca2+ is a primary signaling and regulatory molecule of skeletal muscle (for review, see Ref. 3). It is well known that muscle fiber types express various levels of several Ca2+ storage and transport proteins/mRNAs. Recently, it was reported that transgenic mice expressing a constitutively active form of calcineurin exhibited an increased expression of genes typically expressed in slow muscle (24). Interestingly, our data show that the calcineurin catalytic subunit mRNA was fivefold higher in white muscle. These observations suggest that measurements of total calcineurin protein and phosphorylation in fiber types are required because activated calcineurin produces gene expression associated with slow-twitch muscle fibers, whereas high calcineurin mRNA concentration is associated with white muscle.

Microarray analysis is a powerful tool for determining potential associations between gene expression and phenotypic outcomes. The scope of transcriptional regulation of fiber type may be wider than previously thought, and new mRNAs have been identified with differential expressions in muscle types. Although the multifaceted functions of red and white muscles reflect the differential expression of mRNAs encoding contractile and metabolic proteins between the fiber types, these fibers also differ in signaling and transcription factor mRNA expression. The results of the current study significantly extend our understanding of the molecular diversity of skeletal muscle types, which could have larger implications in muscle type-associated diseases.


    ACKNOWLEDGEMENTS

We acknowledge the extreme generosity of Dr. Eric P. Hoffman and Yi-Wen Chen in aiding with microarray analysis. We thank Drs. Charles Caldwell and Gary Allen as well as Adam Asare, Harpreet Monga, Lillian Folk, and Jeff Fitzgerald for assistance and stimulating discussions concerning bioinformatics.


    FOOTNOTES

This study was supported by American Physiological Society Fellowship in Physiological Genomics (to W. G. Campbell), NASA Postdoctoral Research Associateship (to S. E. Gordon), American College of Sports Medicine Foundation (to C. J. Carlson), and National Institutes of Health Grants HL-57367 (to M. T. Hamilton) and AR-19393 (to F. W. Booth).

Present address of W. G. Campbell: Dept. of Biochemistry, Nova Southeastern Univ., Ft. Lauderdale, FL 33325.

Address for reprint requests and other correspondence: F. W. Booth, Dept. of Veterinary Biomedical Sciences, E102 Veterinary Medical Bldg., 1600 E. Rollins Rd., Univ. of Missouri, Columbia, MO 65211 (E-mail: boothf{at}missouri.edu).

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 1 March 2000; accepted in final form 26 October 2000.


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ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
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