|
|
||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1LIKES Research Center for Sport and Health Sciences; and 2Neuromuscular Research Center, Department of Biology of Physical Activity, University of Jyväskylä, Jyväskylä, Finland
Submitted 13 September 2005 ; accepted in final form 5 December 2005
| ABSTRACT |
|---|
|
|
|---|
collagen; exercise; glycoprotein; proteoglycan
In skeletal muscle, the ECM gives mechanical support to the myofibers during contractions, provides the tissue with elastic properties, and participates in the transmission of force from the myofiber to tendon. The ECM comprises collagens, noncollagenous glycoproteins, and proteoglycans. In skeletal muscle, fibrillar collagens (types I, III, and V) are the main components of the ECM, and type IV collagen is the main component of the BM that surrounds every myofiber connecting the sarcolemma to the ECM. Together with collagens, glycoproteins and proteoglycans form structures and interactions that are significant for myofiber maintenance, structural integrity, and signaling (see reviews in Refs. 22, 24, and 31).
Both endurance and resistance training usually accelerate the biosynthesis of ECM components of skeletal muscle. Several studies have shown an exercise-induced increase in collagen turnover (24), but less is known about the training effect on glycoproteins and proteoglycans. The amount and gene expression of these macromolecules have been shown to increase in muscle and tendon following various types of exercise (15, 29).
Transforming growth factor-
(TGF-
) modulates ECM protein expression via Smad proteins (see revew in Ref. 33). TGF-
is expressed as three isoforms. Their signal is mediated from the extracellular space by receptors to receptor-associated Smads in the cytosol. Receptor-associated Smads bind with common Smad on their way to the nucleus, but inhibitory Smads may interfere with this signal transduction. In addition to TGF-
, connective tissue growth factor (CTGF) is known to regulate ECM gene expression.
The ECM of diabetic skeletal muscle has been little studied. In a study of muscle atrophy in several systemic diseases, e.g., diabetes, Lecker et al. (27) found changes in common in the transcription of some ECM-related genes regardless of the reason for atrophy. By measuring the marker enzymes of collagen biosynthesis, Han et al. (16) suggested that diabetes decreases collagen synthesis, whereas running training (1216 wk) has an increasing effect. However, training as such was able only to a limited extent to prevent changes in the collagen metabolism of diabetic muscle.
There is no comprehensive knowledge regarding diabetes-induced changes in ECM collagens, noncollagenous glycoproteins, and proteoglycans in skeletal muscle. Moreover, it is not known how training affects these proteins in diabetes. The purpose of the present study was therefore to determine 1) whether diabetes affects gene expression of ECM proteins, 2) whether diabetes-induced changes can be restored by training, and 3) whether these changes are explained by mRNA levels of ECM-regulating proteins.
| MATERIALS AND METHODS |
|---|
|
|
|---|
At the age of 10 wk, the animals were randomly assigned to diabetic and control groups. Experimental diabetes, similar to type 1, was induced by a peritoneal injection of streptozotocin (STZ, 180 mg/kg; Sigma-Aldrich, Lyon, France) dissolved in sodium citrate buffer solution (0.1 mol/l, pH 4.5). An equal volume of buffer was injected into the control mice. Mice were characterized as diabetic when their urine glucose values were greater than 200 mg/dl 72 h after the injection of STZ (Glukotest; Roche, Basel, Switzerland). Diabetic mice were not treated with insulin during the study, and they showed symptoms of type 1 diabetes, such as polyuria and weight loss.
Diabetic and healthy animals were randomly assigned to 12 groups (n = 5 per group), which were either sedentary or trained for 1, 3, or 5 wk. Groups were named as follows: sedentary healthy mice (C1, C3, C5), trained healthy mice (T1, T3, T5), sedentary diabetic mice (D1, D3, D5), and trained diabetic mice (DT1, DT3, DT5). Training groups performed treadmill running (21 m/min, 2.5° incline, 1 h/day) for 5 days a week. Animals were weighed once a week during the experiment as well as at the beginning and at the end of the study.
Tissue preparation. Trained mice were euthanized by cervical dislocation 24 h after the last training bout together with their respective sedentary controls. Blood and muscle samples were taken immediately. Calf muscles (soleus, gastrocnemius, and plantaris) were removed, weighed, and frozen in liquid nitrogen. Serum glucose was analyzed with a HemoCue B-Glucose analyzer (HemoCue, Ängleholm, Sweden).
The proximal part (
30 mg) of the right calf muscle complex was homogenized in cold 0.2 M NaCl Tris-buffered solution (pH 7.5). The supernatants were used for the assay of citrate synthase activity as previously described (20). Dissolved muscle protein concentration was measured using the Bio-Rad Protein Assay according to the manufacturers instructions (Bio-Rad, Hercules, CA). Enzyme activities were expressed as units per milligram of dissolved protein.
Total RNA was extracted from the left calf muscle complex with TRIzol Reagent (Invitrogen, Carlsbad, CA) and further purified with RNeasy columns (Qiagen, Valencia, CA) according to the manufacturers protocols. Concentration and purity of RNA were determined by spectrophotometry at wavelengths of 260 and 280 nm. RNA integrity was tested by agarose gel electrophoresis. For the microarray analysis, an equal amount of RNA from each sample was pooled within each group, resulting in 12 arrays. Individual RNA samples were used for the real-time PCR.
Analyses of mRNA expression. Pooled RNA samples were analyzed with an Affymetrix Gene Chip MG U74Av2 (Affymetrix, Santa Clara, CA) representing 6,000 known genes and 6,000 ESTs. The microarray analyses were performed by the Finnish DNA Microarray Center at Turku Center for Biotechnology according to the manufacturers instructions. Arrays were scanned using a GeneArray Scanner G2500A (Agilent, Palo Alto, CA), and images were analyzed with Microarray Suite 5.0 software (Affymetrix). All chips were scaled (global scaling) to the average target intensity of 50 to minimize differences between chips caused by physical differences, hybridization efficiencies, and manual laboratory work. The data were subjected to robust normalization, which reduces errors caused by binding capacity and linearity differences between probe sets. The quality checks recommended by Affymetrix were made to all samples before the comparison analysis to determine differentially expressed genes. The following comparisons were performed using Microarray Suite 5.0: trained (T) vs. control (C), diabetic (D) vs. C, trained diabetic (DT) vs. C, and DT vs. D. The comparisons were done at each time point. Transcripts had to meet multiple criteria before they were regarded as differentially expressed. Changes in expression had to be significant (increased or decreased) according to the Microarray Suite 5.0 algorithms and the two based logarithmic ratio of expressions >0,3 or <0,3. Transcripts had to be at least marginally present in one of the two compared samples, and they also had to be present in at least three samples. GeneSpring 6.1 software (Silicon Genetics, Redwood City, CA) was used in applying the last-mentioned filter and in drawing up the gene lists and the preliminary result tables. The complete data set is publicly available in the NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/; acc. no. GSE1659).
Total RNA (5 µg) was reverse transcribed using a High-Capacity cDNA Archive kit (Applied Biosystems, Foster City, CA) according to the manufacturers instructions. On the basis of the microarray results, four genes were chosen for closer analyses by real-time PCR. Primers were designed for fibulin-2 (X75285
[GenBank]
),
2-chain of laminin-2 (U12147
[GenBank]
),
1-chain of collagen type IV (J04694
[GenBank]
), and
1-chain of type III collagen (BC043089
[GenBank]
). Oligo Exporer software (http://www.uku.fi/
kuulasma/OligoSoftware/index.htm) was used for the primer design (Table 1). A sample of cDNA (5 ng of RNA equivalent) was analyzed with a QuantiTect SYBR Green PCR kit (Qiagen, Hilden, Germany) and ABI Prism 7700 Sequence Detection System (Applied Biosystems). All samples were run at least in duplicate along with the standards. Amplification was performed at the following temperatures: 95°C for 15 min, followed by 40 cycles at 94°C for 15 s, followed by 30 s at annealing temperature, 30 s at 72°C, and finally 15 s at the detection temperature. The annealing and detection temperatures are shown in Table 1. For GAPDH, TaqMan probe-based (Mm99999915_g1) analysis was used. The primer and probe set was purchased from Applied Biosystems, and the conditions they recommended were used for the real-time PCR. Specific mRNAs in the sample were quantified according to the corresponding gene-specific standard curve. To compensate for variations in mRNA quantity and reverse transcription efficiency, the results were normalized to GAPDH. In the microarray data, GAPDH showed the steadiest expression in all conditions when normally used housekeeping genes were compared. The specificity of the amplified target sequence was confirmed on observing a single reaction product of the right size on an agarose gel and a single peak on the DNA melting temperature curve determined at the end of the reaction.
|
0.04 and marginally expressed at 0.04 < P
0.06. Statistical algorithms based on the WSR test were also used to determine significant differential expression in the comparative analyses between treatment groups. Gene expression was deemed significantly increased at P
0.0025 and significantly decreased at P
0.9975. Calculation of the magnitude of the change in expression was based on differences between corresponding probe pair intensities across the two arrays and one-step Tukeys biweight estimate statistics. The aforesaid nonparametric test is suitable for expression analysis due to its insensitivity to the intensities of outlier probe pair (18). | RESULTS |
|---|
|
|
|---|
|
|
|
|
2-chain. The results for the collagen type III
1-chain (Col3a1) and collagen type IV
1-chain (Col4a1) were further verified by the real-time PCR (Fig. 1). The results were well in line with the results of the microarray analyses.
|
2 chain, fibulin-2, and trombospondin-1 in D and DT. mRNA levels of fibrillin-1 and elastin decreased in D (Tables 4 and 5). The gene expression of fibulin-2 (Fbn1), and laminin-
2 chain (Lama2) was further studied by quantitative PCR (Fig. 1). These results were in line with the results of the microarrays, although the changes in fibulin-2 and laminin-2 were not statistically significant due to rather high variation. Proteoglycans. The transcription of decorin and lumican was changed. These two proteins belong to the small leucine-rich proteoglycan (SLRP) family (Table 4). Decorin expression increased in D5 and DT5. Expression of lumican decreased after 1 wk in all groups and increased only in group D5 (Table 5).
TGF-
and CTGF.
The transcription rate of TGF-
isoforms did not change (Table 5). Gene expression of TGF-
2 and TGF-
1 was below the detection limit. Smad proteins mediate TGF-
signaling. The transcription of two receptor-associated Smads (Smad1 and Smad2) as well as of common Smad4, which may form a complex with receptor-associated Smads, increased in diabetic muscle. Exercise was observed to have an attenuating effect in the transcription of Smad2 and Smad4. In addition, the transcription of inhibitory Smad7 tended to increase in D and DT. Expression of receptor-associated Smad5 and inhibitory Smad6 was very low and that of receptor-associated Smad3 was below the detection limit. Diabetes increased the level of CTGF mRNA, but exercise attenuated the increase to the control level in DT1 and DT3.
| DISCUSSION |
|---|
|
|
|---|
-Smad pathway. Some of these effects of diabetes were partially attenuated with training. Training attenuates diabetes-induced decreases in gene expression of collagens. It is well known that the ECM of many tissues is vulnerable to the changes induced by diabetes. In connection with nephropathy and retinopathy, an increase in collagen concentration was observed in the mesangial matrix as well as in the BM of the glomerulus and retina (see reviews in Refs. 2 and 39).
A microarray study revealed that tissues adapt to diabetes by modifying their transcriptome differently (23). In a review of recent studies, the transcription of Col1a1, Col1a2, Col3a1, Col4a1, Col5a1, and Col5a2 was downregulated in skeletal muscles but upregulated in the renal cortex in diabetic rats (23, 27). In the study by Han et al. (16), reduced activity of the collagen biosynthesis enzymes prolyl-4-hydroxylase and galactosylhydroxylysyl glucosyltransferase was found in diabetic skeletal muscles. In their study, physical exercise reduced the changes. An attenuating effect of endurance training was also seen in an ultrastructural study of diabetes-induced increase in collagen fiber cross-sectional area (34).
Endurance training is known to increase collagen synthesis and accumulation in skeletal muscle (25, 36). Transcription of types I and III collagens increases after endurance training (30) and acute physical exercise (17). Postexercise, gene expression of type IV collagen was found to increase even earlier than that of fibrillar collagens (17). In the case of an acute bout of exercise, no effect on the protein levels of types I and III collagens was detected (17). Observations after endurance training continue to be lacking. Endurance training increased concentration of type IV collagen in slow (soleus) but not in fast (rectus femoris) muscle (25). In this study, training had an increasing effect on transcription of few collagen genes in healthy mice but was able to alleviate diabetes-induced decrease of mRNA level of several collagen genes in the diabetic training group.
Our findings of reduced collagen gene expression support previous observations of decreased collagen metabolism in diabetic skeletal muscle (16). Partial attenuation of the diabetic effect was seen in the collagen transcriptions after physical training. Interestingly, in addition to diabetes, transcription of collagen type I and type III is decreased in old age (43).
Diabetes modifies gene expression of several ECM glycoproteins. Laminin-2, thrombospondin-1, and fibulin-2 mediate various cell-to-cell, cell-to-matrix, and matrix-to-matrix interactions, contributing thereby to cell and ECM characteristics (5, 26, 37). Elastin provides flexible properties for the ECM, and microfibrils containing fibrillin-1 help to resist mechanical forces (46).
The amount of laminin (45) and elastin (38) as well as gene expression of thrombospondin-1 (35) increase in diabetic kidneys, whereas gene expression of fibulin-2 is reduced (42). In diabetic muscle, transcription of fibrillin-1 is downregulated (27).
The laminin concentration in the BM is higher in slow than in fast muscles. It has been shown that training has no effect on laminin concentration (25). As far as we know, no studies exist on the effects of exercise on fibulin-2 and fibrillin-1 in skeletal muscle.
In this study, diabetes induced an increase in the gene expression of laminin-2, thrombospondin-1, and fibulin-2 and a decrease in the transcription of elastin and fibrillin-1 (Table 5). Exercise attenuated changes in the mRNA levels of elastin and fibrillin-1. Our laminin, thrombospondin-1, and fibrillin-1 findings correlate well with those of previous studies of diabetic kidneys and skeletal muscle. As in the results for collagen mRNA content, our observations of the changes in elastin and fibulin-2 gene expression in diabetic skeletal muscle were contrary to those obtained from diabetic kidney. Reduced transcription of elastin and fibrillin-1 may, in turn, lead to decreased concentrations of these proteins and thus change the elastic and force-bearing features of the ECM. The novel finding observed in this study was that this diabetes-induced reduction was prevented by physical activity.
Diabetes decreases collagen and increases gene expression of other glycoproteins in the BM. The BM is an active interface between the muscle cell membrane and the ECM. In the present diabetic groups, transcription of collagen types IV and XV decreased and that of laminin-2 and fibulin-2 increased. Previously, type IV collagen content relative to laminin-2 content was shown to be higher in slow (soleus) than in fast (rectus femoris) skeletal muscles (25). These results are in line with the metabolic observations for the same data set studied here. We detected downregulation of genes typical of oxidative muscle cells and of the calcineurin-dependent signaling pathway that upregulates the formation of slow muscle fibers (Silvennoinen M, Kivelä R, Lehti TM, Komulainen J, Kontro H, Vihko V, and Kainulainen H, unpublished observation). The decrease in gene expression of BM collagens and increase in noncollagenous glycoproteins might change the structure of the BM in a less collagenous direction, thus affecting its properties.
Diabetes increases gene expression of small leucine-rich proteoglycans.
The proteoglycans decorin and lumican, whose transcription was affected in diabetic skeletal muscle, are both members of the SLRP family (Table 4). Members of this family are known to interact with TGF-
growth factors (44) and take part in collagen fibril formation (3). Knockout studies have shown that SLRPs regulate collagen fibril formation and prevent lateral fusion of the fibrils (3). In a recent study, an increased level of decorin gene expression was observed in many diabetic tissues (23). Training increased the amount of decorin in tendon (15), whereas the contribution of decorin to skeletal muscle ECM remodeling after physical activity is not well known. In the present study, an increase in the gene expression of decorin and lumican was observed in both the D5 and DT5 groups (Table 5). The increased gene expression of SLRPs may be connected to diabetes-induced changes in the collagen metabolism or TGF-
signaling.
Training attenuates some of the diabetes-induced changes in gene expression of ECM-regulating proteins.
TGF-
and CTGF are growth factors that modulate the ECM. The TGF-
pathway activates collagen expression via Smad proteins (22). Both TGF-
and CTGF are necessary in the activation of fibroblasts and collagen synthesis induced by mechanical loading (12, 13). The synthesis of CTGF itself is activated by mechanical load (32), TGF-
, and advanced glycation end products (AGEs) (40) of which mechanical load has a more prominent effect than TGF-
(22). In this study, the transcription of some TGF-
isoforms was not detected, whereas the rest remained constant in all groups (Table 5). Gene expression of three TGF-
pathway proteins, Smad1, Smad2, and Smad4, increased in the diabetic groups. Diabetes also increased the CTGF mRNA level. An attenuated effect was observed in DT1 and DT3.
The TGF-
pathway may be inhibited by decorin binding to TGF-
(44) or by increased phosphorylation of Smad proteins (1). TGF-
is activated by a tissue-specific activator, thrombospondin-1 (7), which functions in many tissues, e.g., lungs, but not in smooth muscle cells (14) and probably not in skeletal muscle either. The transcription of decorin was increased in D5 as well as in DT5, and thrombospondin-1 at all time points, in D and DT. The mRNA results for CTGF and thrombospondin-1, verified by quantitative PCR, were well in line with the array results (Kivelä R, Silvennoinen M, Touvra A-M, Lehti TM, Kainulainen H, and Vihko V, unpublished observation).
Verrecchia et al. (41) studied which ECM-related genes are activated by TGF-
in human dermal fibroblasts. According to their criteria they named seven genes that were activated through TGF-
Smad3 pathway: Col1a2, Col3a1, Col6a1, Col6a3, and tissue inhibitor of metalloproteases-1 (Timp1) and two additional genes, Col1a1 and Col5a2. These genes, except Timp1 (transcription below detection limit on the microarray), were all downregulated in D and DT in the present study. It seems obvious that the TGF
-Smad3 pathway is downregulated in type 1 diabetic skeletal muscle. The transcription patterns of Eln, Col4a1, Col4a2, Col15a1, and Col26a1 were markedly similar to the previously mentioned collagen genes. Transcription of both Col4a1 and Col1a1 is stimulated by TGF-
but mediated through different pathways (19). Therefore, it would be interesting to study further whether the expression of Eln, Col4a2, Col15a1, and Col26a1 is regulated in the same way as that of Col1a1 or Col4a1.
In addition to TGF
-pathways, formation of AGEs is one of the potential regulating factors of the ECM metabolism in diabetic skeletal muscle. Accumulation of AGEs inhibits collagen synthesis, reduces the collagen turnover rate (8), and increases cross-linking of proteins, thus making the ECM stiffer and less adaptable to the changing conditions. Interestingly, in a high-glucose environment, the glycation of collagen in a tendon proceeds faster than in a normal glucose concentration environment and is discernible within a week (9).
Taken together, it is possible that in diabetic skeletal muscle low levels of TGF-
, incipient AGE formation, and later also decorin cause downregulation of collagen transcription. Physical training, in turn, may decrease AGE formation and thus diminish the inhibition of collagen gene expression.
In conclusion, The present study showed that experimental type 1 diabetes results in changes in the transcription of collagens, noncollagenous glycoproteins, and proteoglycans in skeletal muscle. These changes may cause modifications to the structure and function of the ECM. However, exercise has a beneficial effect on the gene expression of some of these proteins in diabetic skeletal muscle. We suggest that inhibition of the TGF-
-Smad3 pathway is involved in this process. Furthermore, an accumulation of AGEs in diabetic muscle may enforce this downregulation effect. However, our hypotheses and the involvement of other regulatory mechanisms need further investigation.
| GRANTS |
|---|
|
|
|---|
|
| ACKNOWLEDGMENTS |
|---|
| FOOTNOTES |
|---|
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.
| REFERENCES |
|---|
|
|
|---|
and CTGF have overlapping and distinct fibrogenic effects on human renal cells. Am J Physiol Renal Physiol 283: F707F716, 2002.This article has been cited by other articles:
![]() |
T. M. Lehti, M. Silvennoinen, R. Kivela, H. Kainulainen, and J. Komulainen Effects of streptozotocin-induced diabetes and physical training on gene expression of titin-based stretch-sensing complexes in mouse striated muscle Am J Physiol Endocrinol Metab, February 1, 2007; 292(2): E533 - E542. [Abstract] [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Visit Other APS Journals Online |