Absolute Quantitative Profiling of the Key Metabolic Pathways in Slow

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Absolute Quantitative Profiling of the Key Metabolic Pathways in Slow and Fast Skeletal Muscle Dariusz Rakus,† Agnieszka Gizak,† Atul Deshmukh,‡ and Jacek R. Wiśniewski*,‡ †

Department of Animal Molecular Physiology, Wroclaw University, Wroclaw 50-205, Poland Department of Proteomics and Signal Transduction, Max-Planck-Institute of Biochemistry, D-82152 Martinsried, Germany

‡

S Supporting Information *

ABSTRACT: Slow and fast skeletal muscles are composed of, respectively, mainly oxidative and glycolytic muscle fibers, which are the basic cellular motor units of the motility apparatus. They largely differ in excitability, contraction mechanism, and metabolism. Because of their pivotal role in body motion and homeostasis, the skeletal muscles have been extensively studied using biochemical and molecular biology approaches. Here we describe a simple analytical and computational approach to estimate titers of enzymes of basic metabolic pathways and proteins of the contractile machinery in the skeletal muscles. Proteomic analysis of mouse slow and fast muscles allowed estimation of the titers of enzymes involved in the carbohydrate, lipid, and energy metabolism. Notably, we observed that differences observed between the two muscle types occur simultaneously for all proteins involved in a specific process such as glycolysis, free fatty acid catabolism, Krebs cycle, or oxidative phosphorylation. These differences are in a good agreement with the well-established biochemical picture of the muscle types. We show a correlation between maximal activity and the enzyme titer, suggesting that change in enzyme concentration is a good proxy for its catalytic potential in vivo. As a consequence, proteomic profiling of enzyme titers can be used to monitor metabolic changes in cells. Additionally, quantitative data of structural proteins allowed studying muscle type specific cell architecture and its remodeling. The presented proteomic approach can be applied to study metabolism in any other tissue or cell line. KEYWORDS: glycolysis, fatty acid metabolism, carbohydrate metabolism, energy metabolism, label free quantitative proteomics, “total protein approach”, filter aided sample preparation, absolute protein quantitation

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INTRODUCTION Skeletal muscles, the largest organ in a mammalian body, play indispensable roles in the body motion and maintenance of the whole organism metabolism. Muscles are composed of fibers with distinct physiological properties. On the basis of biochemical studies on oxidative and glycolytic enzymes as well as on histochemical and physiological analyses, muscle fibers are broadly classified into slow, oxidative (type I) and fast, glycolytic (type II) fibers.1 The key differences between both fiber types are their metabolism and the composition of their contractile machinery, the sarcomere. Whereas in muscles composed mainly of slow fibers oxidative phosphorylation is © XXXX American Chemical Society

the major source of ATP, in muscles built predominantly of fast fibers ATP production is largely shifted to glycolysis.2,3 The proportion of the slow and fast fiber types determines the functional properties of a muscle−like contraction speed and resistance to fatigue, and allows different muscle groups to perform specific tasks in a body. On the other hand, differences in physical performance (endurance and strength) are an outcome of the variation in the fiber type content within a given muscle. Responding to exercise, neuronal stimulation and Received: October 6, 2014

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DOI: 10.1021/pr5010357 J. Proteome Res. XXXX, XXX, XXX−XXX

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Journal of Proteome Research hormones muscle fibers can alter their phenotype and thus, skeletal muscle can undergo remodeling to meet new functional and physiological demands. Studies have revealed that endurance athletes have relatively more slow fibers whereas the musculature of the sprinters is predominantly composed of fast fibers.4 Fiber type composition of the musculature might be directly correlated with a risk of certain chronic diseases. It has been demonstrated that in patients with Duchenne muscular dystrophy, fast fibers are more susceptible to degenerative changes (for review see: ref 5). Reduced amount of slow fibers within muscle mass might contribute to insulin resistance and increases risk of obesity.5 Moreover, muscles of type 2 diabetic patients show reduced oxidative enzymes activity which is most likely due to a reduction in slow oxidative fibers.6 Therefore, precise characterization of muscle composition might help to identify potential therapeutic targets, thus contributing to improvement of prevention and diagnosis of metabolic diseases. Traditionally, skeletal muscles have been studied using biochemical and immunological techniques. These, often laborious approaches, are limited to simultaneous analysis of a limited number of enzymes or proteins.7 Microarray based expression profiling allows monitoring of the levels of mRNAs,8,9 but these data cannot be directly translated into proteins concentrations. In contrast, the proteomics technologies have the potential to provide in-depth insights in the muscle organization and dynamics of thousands of proteins in a single experiment. Previous studies have already demonstrated that the muscle tissue can be studied by proteomics using isotope labeling as well as label free techniques. Different labeling technologies enabled relative quantitation of proteins between different samples including profiling differences between slow and fast muscle types,10 alterations in progress of skeletal muscle aging,11 changes of the muscle metabolism in α-laminin deficient animals,12 and proteomic insights of muscle pathologies.13,14 Recently, the potential of the label-free techniques for quantitative profiling of muscle proteomes was demonstrated by Burniston et al.15 Here, we analyze two mouse muscles: gastrocnemius (i.e., its so-called white part, composed mainly of glycolytic, fast-twitch fibers) and soleus (red muscle, containing mainly oxidative, slow-twitch fibers), and determine their protein composition. Taking advantages of the MED-FASP (Multienzyme digestionfilter aided sample preparation) sample processing16 and the computational “total protein approach”17 and the “proteomic ruler” method,18 we provide titers of more than 1000 proteins covering comprehensively members of all basic metabolic pathways and the contractile machinery in fast and slow muscles. Notably, our approach does not require sample labeling and any newest mass spectrometry technology. Our study is a steady-state-comparison of two muscle types, but the presented approach can be applied as well to monitor changes upon any physiological perturbation. The physiological meaning of the quantitative data presented here is discussed.

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(IKA Labotechnik) in ice-cold buffer: 20 mM Tris-HCl, 1 mM EDTA, 1 mM EGTA, 1 mM DTT, 1 mM PMSF, pH 7.4, 4 °C. For the proteomic analysis, protein extracts were supplemented with SDS and DTT to final concentrations of 2% and 0.05 M, respectively. The protein lysates were boiled at 100 °C, for 5 min. Total protein was determined by measuring tryptophan fluorescence as previously described.19 Comparison of Protein Extraction Efficiencies of Various Reagents

Aliquots of whole muscle homogenates and HeLa cell membrane fraction, containing 1 mg of total protein in 0.2 mL, were solubilized using 1% SDS, 1% sodium deoxycholate, 1% sodium laurate, or 6 M guanidine HCl at 100 °C for 5 min. After the mixture was chilled to room temperature, the remaining insoluble material was collected by centrifugation at 16 000g for 10 min and the pellets were re-extracted with 1% SDS. Protein contents in the primary and the secondary extracts were determined as indicated above. Enzyme Activity Assays

Muscle homogenates were centrifuged at 20 000g at 4 °C, for 20 min. The supernatants were assayed for activities of the key enzymes from glycolysis and gluconeogenesis pathways. Enzyme activities were determined from the difference in the slope of NAD(P)H absorbance (340 nm; λ = 6.22 mM−1 cm−1) before and after addition of the substrate. The activities, unless stated otherwise, were measured in 50 mM bis-Tris-propane buffers with 150 mM KCl, 0.25 mM EDTA and 5.25 mM MgCl2, pH 7.4, at 37 °C based on the assays described by Teusink et al.20 The phosphofructokinase (Pfk) reaction mixture contained 0.01 mM fructose-2,6-bisphosphate (F2,6P2), 0.2 mM NADH, 10 mM fructose-6-phosphate (F6P), 5 U mL glycerol-3-phosphate dehydrogenase (Gpd), 5 U aldolase (Aldo), 5 U triose phosphate isomerase (Tpi), 3 mM DTT, 0.02 mM AMP, and 2 mM ATP; KCl concentration was 100 mM. The aldolase reaction mixture contained 0.2 mM NADH, 5 U Gpd, 5 U Tpi and 1.0 mM fructose-1,6bisphosphate (F1,6P2). The lactate dehydrogenase (Ldh) reaction mixture contained 0.2 mM NADH and 2 mM pyruvate; MgCl2 concentration was 10.25 mM, and 100 mM NaCl was used in a buffer instead KCl. The fructose 1,6bisphosphatase (Fbp) reaction mixture contained 0.2 mM NADP, 2 U glucose-6-phosphate dehydrogenase, 2 U glucose6-phosphate isomerase (Gpi), and 0.2 mM F1,6P2; the concentration of MgCl2 was 1.25 mM. Western Blot Analysis

The lysates of muscle samples were electrophoresed, transferred to nitrocellulose, and probed as described previously.21 Briefly, aliquots of whole tissue lysates containing 10 μg of total protein were separated on SDS gels and were blotted onto nitrocellulose. After protein fixation with 0.5% glutaraldehyde the blots were stained with Poceau S to test the quality of the protein transfer. An antibody stripping procedure allowed using individual blots up to 4 times. The following antibodies were used: rabbit anti-Hk2 (Millipore/Chemicom), anti-Cs (Sigma), anti-Acsl1 (Cell Signaling), goat anti-PK (Acris Antibodies GMBH), and ATP5a (Invitrogen). Antibodies against Aldo, Fbp, and Pgam were produced and purified as described previously.22

EXPERIMENTAL PROCEDURES

Isolation and Lysis of Gastrocnemius and Soleus Muscles

Ten-week-old female C57BL/6 mice were bred on a 12:12-h light-dark cycle and had free access to standard chow diet. The soleus and the superficial, white part of gastrocnemius muscles were dissected from sacrificed mice. The muscle samples were taken from 4 animals and they were analyzed separately. Muscle samples were homogenized with Ultra Turrax T8 homogenizer

Protein Digestion and Peptide Fractionation

Protein lysates from fast and slow muscles were processed in the 30K filtration units (Millipore) using the MED-FASP B


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Figure 1. (A) Proteomic workflow. Muscle tissue was solubilized in in 2% SDS and the extracted proteins were processed by MED-FASP procedure. Peptides were analyzed on LTQ-Orbitrap instruments. Spectra were searched and analyzed using MaxQuant software. The protein intensities were processed by total protein approach and the proteomic ruler. The significance of differences in the protein titers was subjected to multiple hypothesis testing. (B) Principal component analysis of the proteomic data. (C) Selection of the protein extraction reagent. The bars show the content of protein remaining in the insoluble fraction after extraction of whole muscle homogenates and HeLa cell membrane fraction with 1% SDS, 1% sodium deoxycholate, 1% sodium laurate, or 6 M guanidine HCl.

protocol.16 Endoproteinase Lys-C and trypsin were used for sequential digestion of proteins. The enzyme to protein ratios were 1/50. Peptides were quantified as described previously.19 Quadruplets of each sample were prepared and analyzed.

parameter were 90 s and 5 ppm. The MS2 spectra were acquired in the ion-trap. Data Analysis

The MS data was analyzed in MaxQuant software (version 1.2.6.20) using Andromeda search engine.24,25 Proteins were identified by searching MS and MS/MS data of peptides against a decoy version of the UniProtKB (May 2013) containing 50 807 sequences. Carbamidomethylation of cysteines was set as a fixed modification. N-terminal acetylation and oxidation of methionines were set as variable modifications. Up to two missed cleavages were allowed. The initial allowed mass deviation of the precursor ion was up to 6 ppm and for the fragment masses it was 0.5 Da. Mass accuracy of the precursor ions was improved by time-dependent recalibration algorithms of MaxQuant. The “match between runs” option enabled to match identifications across samples within a time window of 2 min of the aligned retention times. The maximum false peptide discovery rate was specified as 0.01. The identified peptides and proteins are listed in the Supporting Information Tables 1 and 2, respectively. Protein titers were calculated on the basis of the raw spectral protein intensity using the Total Protein Approach (TPA)17 and the relationships:

LC−MS/MS Analysis

Analysis of the peptide mixtures was performed in Orbitrap instrument (Thermo Fisher Scientific, Germany) as described previously.23 Briefly, aliquots containing 6−8 μg of peptides were injected and separated on a reverse phase column (20 cm × 75 μm inner diameter) packed with 1.8 μm C18 particles (Dr. Maisch GmbH, Ammerbuch-Entringen, Germany) using a 4 h acetonitrile gradient in 0.1% formic acid at a flow rate of 250 nL/min. The LC was coupled to a LTQ Orbitrap mass spectrometer (Thermo Fisher Scientific, Germany) via a nanoelectrospray source (Proxeon Biosystems, now Thermo Fisher Scientific). The LTQ orbitrap was operated in data dependent mode with survey scans acquired at a resolution of resolution of 60 000 at m/z 400. For CID fragmentation up to the 10 most abundant precursor ions from the survey scan with charge ≥ +2 within 300−1700 m/z range were selected. The normalized collision energy was 35. The dynamic exclusion C


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Figure 2. Proteome based virtual cell architecture. (A) Total protein content per cell nucleus calculated using the “histone ruler” method. (B). Total protein content of proteins matching selected categories of Gene Ontology. (C) Abundance of the contractile proteins. (D) Concentrations of the myoglobin and myosin isoforms. (E) Abundance of proteins of energy metabolism. Carbohydrate metabolism refers to the sum of abundances of proteins directly involved the glycolysis, glycogen metabolism, and pentose phosphate pathway. Purple bars, slow muscle; orange bars, fast muscles.

Protein abundance (i) =

titer differences between the slow and fast muscles (Supporting Information Table 2). Principal component analysis revealed well separation of the data from the two types of samples (Figure 1B). In this study, the calculations of the protein concentrations and the estimation of total protein per cell nucleus are based on identification of 14600 ± 376 and 12330 ± 680 peptides in the slow and fast muscle samples (Supporting Information Table 1). Metabolic enzymes which titers are discussed in this study were well covered by many peptides, and therefore, the values obtained by TPA should be accurate.18 Moreover, previously we have demonstrated that this depth is sufficient for calculation of protein copy numbers.18 Efficient protein extraction is a prerequisite for quantitative proteomic analysis. Several recent studies suggested that various reagents such as Na-deoxycholate, Na-laurate,26 or guanidine hydrochloride27 can be used for protein extraction without compromising lower protein extraction efficiency. To select the optimal conditions for preparation of lysates, we compared the efficiencies of these reagents. Quantitation of the total extracted protein revealed that all reagents extract similarly within ±10% variation amounts of protein from tissue. But when we reextracted the left nonsolubilized material of each extraction with SDS, we were able to extract 2−10% of the initially yielded protein (Figure 1C). The experiment revealed that in comparison to SDS extraction the tissue lysis with Nadeoxycholate or guanidinium hydrochloride was mostly incomplete. Our results well agree with previous studies that showed that SDS provides highest protein extraction yields,28 and therefore, we used SDS as the muscle tissue lysing regent in our experiments.

MS − signal (i) × 100 [%] Total MS − signal

or c(i) =

⎤ ⎡ MS − signal(i) mol ⎥ ⎢ Total MS − signal × MW(i) ⎣ g total protein ⎦

Total protein content per nucleus was calculated using the “histone ruler” method18 using the relationship: Protein/ nucleus =

5.6 pg × Total MS − signal [pg] MS − signal (Total histone)

The calculations were performed in Microsoft Excel. The complete data are shown in Supporting Information Table S2. The total protein of functional categories was calculated by summing the total protein content of arbitrary selected proteins (Supporting Information Table 3). The total protein content of nuclei was obtained by summing the total protein content of proteins matching Gene Ontology categories. according to the relationship: {Nucleus} ∉ [{Endoplasmic reticulum}

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∪ {Contractile fiber part} ∪ {Glycolysis}]

RESULTS AND DISCUSSION

Protein Extraction and the Proteomic Workflow

Protein extracts prepared from 4 animals were processed by MED FASP, a protein cleavage procedure allowing consecutive digestion of proteins with two or more proteases. Advantages of this method over digesting with only one enzyme are the generation of peptide fractions with only little overlap, thus contributing to peptide fractionation, which results in a substantial increase of the number of peptide and protein identifications. The peptide fractions were analyzed using LTQOrbitrap instruments (Figure 1A). The spectra were searched and analyzed using MaxQuant software. The protein intensities (cumulative peptide intensities) were used to calculate protein concentrations in the tissue. Multivariate analysis of the data allowed determination of statistical significances in the protein

Proteomics View of Slow and Fast Muscle Composition

Analysis of the proteomic data revealed similar total protein content of about 2 ng per cell nucleus in fibers composing both the slow29 soleus and fast (white) part of gastrocnemius muscle (Figure 2A). Assuming an average total protein concentration in eukaryotic cells of 20% (m/v)30 and approximately 100 nuclei per cell,31 the estimated volume of a fiber cell is about 1 nL. Using the protein Gene Ontology annotations, we summed the total content of proteins belonging to the main organelles. The slow-twitch muscle contained about 2-fold more D


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Figure 3. Titers of enzymes correlate with their Amax activity. (A) Amax of the enzyme activities and (B) concentration of 1-phospho-fructokinase (Pfkm), lactate dehydrogenase A (Ldha), aldolase A (Aldoa), and fructose-1,6-bisphophatase 2 (Fbp 2). (C) Western blot analysis of lysates of the slow and fast muscle lysates. The blots were probed with antibodies against selected enzymes involved in the glycolysis (hexokinase 2, Hk2; aldolase, Aldo; phosphoglycerate mutase, Pgam; pyruvate kinase, Pk), gluconeogenesis (fructose bis-phosphatase, FBP), Krebs cycle (citrate synthase, Cs), lipid metabolism (fatty acid-CoA ligase 1, Acsl1), and oxidative phosphorylation (ATP synthase subunit α, Atpa1). Asterisks indicate significant differences as calculated by multiple hypothesis testing with the threshold value of 0.05.

metabolites altering enzyme properties, it is to expect that the kinetic data not always can correlate well with the enzyme titer. Nonetheless, our results suggest that changes in enzyme concentration can be used for studying alterations in an enzyme catalytic potential in vivo. The alterations in the titers of Aldo and Fbp between the slow and fast muscle were well reflected by Western blotting (Figure 3C). Figure 3C provides also Western blots analysis of enzymes involved in glycolysis, Krebs cycle, free fatty acids metabolism, and oxidative phosphorylation. These blots validate the titer differences between the muscle types, which were calculated by TPA (Supporting Information Table 1 and the figures below).

mitochondria than the fast-twitch muscle (Figure 2B). In contrast, the differences for nucleus, Golgi, ER and cytoskeleton were negligible. Next we found that the major components of the contractile system constitute about 50% of the total protein in the muscle fibers. The summed abundances of the basic types of contractile proteins were similar in both muscle types (Figure 2C). However, a detailed analysis of myosin heavy chain isoforms revealed a well-known fiber type specific pattern (Figure 2D). The slow muscle contained several-fold more Myh1, Myh2, and Myh7 than the fast one. In contrast, we measured two times higher titer of Myh4 in the fast-twitch muscle. Finally, the abundance of the myoglobin was three times higher in the slow-twitch muscle. Subsequently, enzymes involved in energy metabolism constitute the second highly abundant component of the muscle fibers (Figure 2E). In the fast muscle, proteins of the carbohydrate metabolism constitute more than 13% of total protein, while the glycolytic enzymes contribute 10% of total protein. The lipid metabolism (mainly the β-oxidation), Krebs cycle, and oxidative phosphorylation together represent 10% and 5% of the total protein in the slow and fast muscle, respectively. Notably, the cumulative total protein abundance of mitochondrial proteins (Figure 2B) and the enzymes involved in energy metabolism (Figure 2E) represents about 40% of the protein mass of the slow and fast muscle.

The Fate of Glucose Molecule: Glycolysis, Glycogen Synthesis, and Pentose Phosphate Pathway

Glycolysis is a basic and evolutionary primeval pathway in which glucose molecule may be oxidized under anaerobic conditions giving ATP and the reducing force, NADH. Our quantitative analysis of glycolytic enzymes showed that the titer of practically all glycolytic enzymes was significantly higher in the fast-twitch muscle than in the slow-twitch one (Figure 4A). The only exception was the hexokinase (Hk2) which abundance was at least 2-fold higher in the slow-twitch muscle. This result, along with the elevated expression of glucose transporter Slc2a4 (also known as a Glut4), suggests that the ability of the red muscle to utilize glucose is higher. This is in line with observations that the red, slow-twitch muscle fibers are more efficient than the fast-twitch ones in removing of glucose from blood.32 However, it raises a question about the fate of glucose-6-phosphate molecules in the slow-twitch muscle which, compared with the fast-twitch muscle, possesses lower capacity to oxidize glucose in glycolysis (Figure 4A). Presumably, the higher uptake and phosphorylation of glucose is needed for the enzymes of the pentose phosphate pathway (PPP) and the glycogen synthase (Gys1) which titer in the red muscle was about two times higher than that in the white (Figure 4B,C). Supposedly, the elevation of PPP activity and hence NADPH production is an adaptation of the slow muscles to oxidative metabolism. NADPH serves as a cofactor for reducing of glutathione, which is the most abundant and efficient scavenger

Protein Abundance Detected by Mass Spectrometry Reflect Maximal Enzymatic Activities

In general, titers of enzymes cannot be directly related to their activity. However, it could be expected that their amounts reflect the mid- and long-term requirements of the cell. To compare the relation between the concentration and activity of individual enzymes in the two muscle types, we measured the maximal activities of Pfk, Aldo, Ldh, and Fbp (Figure 3A) and compared these values with their titers (Figure 3B). We observed that the differences of enzyme concentrations assessed from the proteomic data correspond to changes in the enzymatic activities. Since measurements of enzyme activities in tissue extracts can be affected by many factors including sample dilution resulting in dissociation of enzyme complexes, post-translational modifications, and the presence of E


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monomers of enzymes that catalyze the reactions of triose phosphates part of glycolysis. Similar titers of enzymes catalyzing the subsequent reactions of triose phosphates metabolism supports the idea of supramolecular assemblies of glycolytic enzymes in skeletal muscle. And over the past decade, it has been demonstrated that glycolytic enzymes may form active macromolecular complexes and that disruption of such complexes leads to inhibition of glycolysis and energy production in striated muscles35 and in some cancer cell lines.36 The existence of metabolically active complex containing glycolytic enzymes from Aldoa to muscle isozyme of pyruvate kinase (Pkm1) is a promising idea explaining rapid acceleration and cessation of glycolysis, especially in white fibers, during muscle contractions. It has been shown that glycolytic flux in muscle declined rapidly after exercise stops, although the availability of hexose phosphates levels remained high.37 Several lines of evidence show that calcium cations strongly stimulate glycolysis via initiation of association of practically all glycolytic enzymes with contractile proteins [for review see refs 38−40]. It has been proposed that Ca2+−calmodulin may stimulate phosphorylation and/or may interact directly with glycolyic enzymes playing a crucial role in the formation of glycolytic complex.41,42 Assuming this, it might be hypothesized that a fall in [Ca2+] after exercise would lead to disruption of such complex and to a decrease in glycolytic rate. Despite several studies showing the existence of metabolic macrocomplex in glycolysis there is, as of yet, no data on its stoichiometry. Although our data are in line with an idea of “linear” composition of glycolytic complex, which suggest that it contains a similar number of molecules of each enzyme, the precise information on its stoichiometry may be given only after isolation of such complex. The largest difficulty in the isolation would probably be related to high instability of glycolytic complex and thus, several chemical methods (e.g., crosslinking) would be tested to stabilize its composition. However, such treatment usually affects the activity of enzymes (even after removal of a cross-linker) making the measurements of their activities unreliable. Therefore, in this case the quantitative MS analysis seems to be the most appropriate approach to study the complex composition. As an acceleration of glycolysis in response to exercise is much stronger in the fast-twitch fibers, which are the main components of the white muscles, compared with red ones; therefore, it is expected that the titer of calmodulin and calcium-dependent protein kinases, e.g., calcium/calmodulindependent protein kinases (Camk) must be higher in the white muscles. Accordingly, in this study, we found that concentrations of calmodulin and all subunits of Camk2 were significantly higher in the fast-twitch muscle (Figure 4D). On the other hand, it is well documented that the regulation of the glucose flux through glycolysis is also related to the activity of Pfk, especially via the binding of fructose-2,6bisphosphate (F2,6P 2 ), an allosteric activator of the enzyme.43−45 Unexpectedly, we found that the titer of Pfkfb1, a bifunctional enzyme involved in the synthesis and degradation of F2,6P2 was about three times higher in the red muscle. This suggests that the slow-twitch fibers have a higher ability to stimulate Pfk, and hence glycolysis, than does the fast-twitch muscle. However, this goes against the general belief that the rapid acceleration of glycolytic flux is characteristic of the white, fast-twitching fibers. This discrepancy may be explained by the idea of supramolecular organization of glycolysis which suggests

Figure 4. Concentrations of proteins involved in carbohydrate metabolism of (A) glycolysis; (B) pentose phosphate pathway (glutathione reductase (Gsr) is not a part of the pentose phosphate pathway); (C) glycogen metabolism; (D) carbohydrate metabolism regulation. The concentrations of the glycolytic enzymes are given according their quaternary structure compositions. Purple bars, slow muscles; orange bars, fast muscles. Asterisks indicate significant differences as calculated by multiple hypothesis testing with the threshold value of 0.05.

of hydrogen peroxide. Thus, our supposition is in line with earlier studies showing that the level of reduced glutathione is higher in the aerobic slow fibers than in the anaerobic fast fibers.33 Our analysis revealed that the amount of glutathione reductase (Gsr), the enzyme which catalyzes the reduction of oxidized glutathione, was about four times higher in the red muscle as compared to the white (Figure 4B). It is a common belief that activity of three enzymes: Hk, phosphofructokinase (Pfk) and pyruvate kinase (Pk) is crucial for regulation of the glycolytic pathway. We found that the concentration of Pfk was significantly lower than the concentrations of other enzymes catalyzing the subsequent steps in glycolysis, both in the red and white muscle (Figure 4A). The titer of the active oligomers of enzymes involved in triose phosphates metabolism was usually 4−8 times higher than the titer of Pfk tetramer (Figure 4A) and was in the range of 0.015−0.030 mM (assuming an average total protein concentration in eukaryotic cells of 20% (m/v)). These values are similar to those found by Maughan and collaborators in diffusible fraction of the rabbit psoas muscle34 whose proteomic studies revealed an average concentration of 0.08 mM for the F


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Journal of Proteome Research that the rate of glycolysis is primarily regulated by formation of the metabolic complex consisting of triose phosphates metabolism enzymes.35−38 Although we claim that F2,6P2 activation is not likely to be involved largely in the rapid acceleration of glycolysis, it seems that its low concentration might be related to the fast cessation of glycolytic flux in white muscles. This hypothesis is supported by the fact that the concentration of TIGAR protein, an enzyme which hydrolyses F2,6P2, was much higher in the fast muscle than in the slow (Figure 4D). The inhibition of glycolysis is a mechanism redirecting glucose-6-phosphate from being oxidized in glycolysis to PPP (for review see ref 46). We found that the concentrations of PPP enzymes in both the muscle types were several-fold lower than those of glycolytic pathway (Figure 4A,B) and thus, the block of glycolysis is supposedly prerequisite for protection of glucose-6-phosphate for PPP. Lactate Synthesis and Pyruvate Dehydrogenase Complex

The final product of glycolysis, pyruvate, can be oxidized in mitochondria or reduced to lactate by lactate dehydrogenase (by Ldha isozyme) and released out of cell through monocarboxylate transporter, Mct4.47−50 Several studies also revealed that the slow-twitch muscles may uptake lactate via Mct149 and convert it into pyruvate using Ldhb isoform of lactate dehydrogenase.48 Our analysis demonstrated that the fast-twitch muscle expressed huge amount of Ldha compared to Ldhb, while the slow-twitch muscle possessed relatively similar concentrations of both the isoforms (LdhaA and Ldhb) (Figure 5A). These results suggest that the slow-twitch fibers might oxidize as well as reduce the lactate as oppose to fast-twitch fibers which predominantly release lactate out of the cell. The concentrations of the Ldh isoforms are in accordance with the abundance of Mct transporters (Figure 5A). Evidently, the fast-twitch muscles, composed predominantly of glycolytic fibers, are dedicated to reduce pyruvate and release lactate outside the fibers, whereas the slow muscles may both release lactate and absorb it from the blood and/or extracellular fluid. As one might expect, the concentration of all components of pyruvate dehydrogenase complex (PDC), which decarboxylates pyruvate into acetyl-CoA, was at least two times higher in the red than in the white muscle (Figure 5B). Interestingly, we also found that the slow-twitch, but not the fast-twitch, muscle contained mitochondrial D-lactate dehydrogenase, an enzyme which converts D-lactate into pyruvate. Generally, D-lactate is formed via methylglyoxal, which is a cytotoxic side product of several reactions such as nonenzymatic phosphate elimination from glyceraldehyde phosphate and dihydroxyacetone phosphate or lipid peroxidation. However, the titer of Ldhd was significantly lower than that of other Ldh isoforms, which suggest the small importance of methylgyoxal as an energetic substrate for the muscle fibers, and presumably, Ldhd plays a role in the detoxification from methylglyoxal.

Figure 5. (A) Lactate metabolism and transport: (B) pyruvate dehydrogenase complex: (C) creatine and adenylate kinases and AMP deaminase: (D) glycerol phosphate shuttle: (E) malate−aspartate shuttle. Purple bars, slow muscles; orange bars, fast muscles. Asterisks indicate significant differences as calculated by multiple hypothesis testing with the threshold value of 0.05.

has been also reported that insulin treatment in striated muscle inhibits Gsk3b kinase52 and elevates the calcium level,53 which in turn leads to down-regulation of glyconeogenesis. We observed about three times higher concentration of fructose1,6-bisphosphatase (Fbp2), a regulatory enzyme of glycogen synthesis from noncarbohydrates, in the white muscle compared to red muscle. This is in agreement with results of Donovan and Pagliassotti54 who found that in rats, glyconeogenesis operates only in the fast fibers. Glycogen Synthesis and Phosphorolysis

The rate-limiting enzymes in glycogen synthesis and degradation are, respectively, muscle isoform of glycogen synthase (Gys1) and glycogen phosphorylase (Pygm). The activity of these enzymes is regulated reciprocally by allosteric effectors and phosphorylation by protein kinases, such as glycogen synthase kinase 3 (Gsk3b), Ca2+-activated protein kinase and/ or AMP-activated protein kinase (Prkaa) [for review see ref 55]. Several studies have revealed that the fast and slow-twitch muscles differ in their capacity for glycogen deposition and in regulation of glycogen storage.56−58 The capacities of mouse muscles investigated in this study for glycogen synthesis were similar (Figure 5C). Whereas the titer

Glyconeogenesis

For years it was a common belief that lactate produced by working muscle is transported to the liver where it is converted to glucose, which is then transported back to the muscle (’’the Cori cycle’’). However, evidence has accumulated that in skeletal muscle up to 50% of lactate is converted to glycogen.51 This suggests that glyconeogenesis, the glycogen synthesis from noncarbohydrates, significantly contributes to the maintenance of energy stores in vertebrate striated muscles. Just recently, it G


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Figure 6. Concentrations of the key enzymes of the (A) free fatty acid metabolism, (B) Krebs cycle, and (C) oxidative phosphorylation. The total protein values of the oxidative phosphorylation complexes refer to the sum of all subunits. Purple bars, slow muscles; orange bars, fast muscles. Asterisks indicate significant differences as calculated by multiple hypothesis testing with the threshold value of 0.05.

skeletal muscles.61 It is generally believed that high activity of the aforementioned enzymes, especially their cytoplasmic forms, is indispensable for the fast fibers to support myofibrilliar ATPase during intense activity (for review see ref 61). On the other hand, it was hypothesized that the mitochondrial forms of these enzymes, Ckmt2 and Ak2, should be more abundant in the slow fibers, because of their aerobic metabolism. Our quantitative analysis roughly supports this idea. We observed much higher expression of Ckm, Ak1, and Ampdk1 in fasttwitch muscle, while the titer of the mitochondrial forms was higher in the slow one (Figure 5C). However, it is worthy to note that the concentration of the cytoplasmic Ckm and Ak1 in the slow muscle significantly exceeded concentration of any other metabolic enzymes indicating that phosphocreatine− creatine shuttle plays a crucial role also in the slow muscles.

of Gys1 and UTP-glucose-1-phosphate uridylyltransferase (Ugp2) was about two times higher in the slow muscle, the concentration of glycogenin (Gyg1) was practically equal in the both types of muscles. On the other hand, the level of the enzyme which converts a glycolytic intermediate, G6P, into glucose-1-phosphate was much higher in the fast muscle. From this, it is evident that the differences in the amount of synthesized glycogen must result from the different regulation of glycogen synthesis. And indeed, we found that the concentrations of proteins regulating the activity of glycogen metabolism machinery significantly varied between the muscle types. Our analysis revealed that the concentration of GSK3b, a kinase regulated by extracellular signals (primarily insulinmediated) was much higher in the red muscle, whereas proteins sensitive to the metabolic state of a cell (e.g., Prkaa2) and/or muscle contraction, calcium concentration (Calm, Camk2) were abundantly expressed in the white muscle (Figure 5C,D). The biochemical and proteomic analysis of various skeletal muscles has revealed that the fast-twitch muscles contain high concentrations of enzymes involved in glycogen breakdown,59 which correlates with a marked decrease in glycogen content in response to high intensity exercise60 (for review see ref 51). The analysis presented here is in agreement with these reports: we found that the titer of glycogen phosphorylase (Pygm) was 2-fold higher in the fast than that in the slow muscle (Figure 4C), which emphasizes the role of glycogen as a main source of glucosyl units during short and intense exercise.

Transport of Reducing Equivalents to Mitochondria

The malate−aspartate shuttle (MA-shuttle) and the glycerol-3phosphate shuttle (GP-shuttle) are the mechanisms which regenerate NAD from NADH and translocate electrons produced in cytoplasm (e.g., in glycolysis) to mitochondria for oxidative phosphorylation. It is a common belief that GPshuttle is only secondary to MA-shuttle. This is because the equimolar amount of the both components of GP-shuttle (cytosolic and mitochondrial glycerol 3-phosphate dehydrogenases: Gpd1 and Gpd2, respectively) is required for its functionality, whereas in most tissues the titer of Gpd2 is several times lower than that of Gpd1 [for review see ref 62]. In line with this, we found that the concentration of Gpd2 was about 20 times lower than that of Gpd1, which excluded the possibility of efficient transport of reducing equivalents via GPshuttle in both types of mouse muscles (Figure 5D). However, we found that Gpd1 was highly abundant protein both in the slow-twitch and fast-twitch muscle, although its level was more

Phosphocreatine−Creatine Shuttle

Phosphocreatine kinase (the cytoplasmic form, Ckm, and the mitochondrial enzyme, Ckmt2), adenylate kinase (the cytoplasmic Ak1 and mitochondrial Ak2) and AMP deaminase (Ampd1) play an important role in buffering ATP level, both in cytoplasm and in mitochondria, and fueling contraction in H


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Figure 7. Summary of the energy metabolism in the slow and fast muscle fibers. The width of the arrows or blocs is proportional to the concentration of the enzymes and transporter proteins. The width of the arrows and boxes for the β-oxidation, pyruvate dehydrogenase complex, and oxidative phosphorylation complexes reflect the average concentration of their basic components. The arrows of the Glut4 and the MCT transporters are not scaled due to their relative low titers.

for ATP regeneration in the slow-twitch muscle. In both muscle types, the titers of the peroxisomal enzymes of the β-oxidation, Acyl-Co oxidase, enoyl-CoA-hydratase/hydroxy-Acyl-CoA-dehydrogenase, and 3-ketoacyl CoA thiolase, were negligibly low (Supporting Information Table 1). Similarly, the enzymes of FFA and triglyceride synthesis were at very low levels or escaped detection indicating minor importance of these processes in the muscle fibers.

significantly elevated in the fast-twitch muscle. This is in agreement with the previous studies of MacDonald and Marshall63 and Okamura et al.59 who found that the level of Gpd1 in rats is much higher in extensor digitorum longus muscle (consisting mainly of fast fibers) than in soleus. Presumably, cytoplasmic Gpd1 eliminates the necessity of coupling of Gapdh and Ldha activities that is needed to ensure NAD for intense glycolysis in the fast fibers. Evidently in mouse skeletal muscle, like in most vertebrate tissues, MA-shuttle dominated over GP-shuttle.62 Unexpectedly, we found that all components of MA-shuttle (Mdh1, Mdh2, Got1 and Got2) were expressed at high level not only in the red muscle, but also in the white (Figure 5E). This suggests that mitochondrial oxidation of NADH plays an important role in both red and white muscle metabolism.

Krebs Cycle and Oxidative Phosphorylation

Our analysis revealed that the titers of all proteins of the Krebs cycle and oxidative phosphorylation were about two times higher in the slow-twitch muscle (Figure 6B,C). It raises a question whether the different capacity of the red and white fibers to oxidative metabolism is related to changes in mitochondria structure or merely in the amount of mitochondria. Studying distribution of proteins across various subcellular structures and organelles, we observed that the total abundance of mitochondrial proteins was two times higher in the red than in white muscle (Figure 1B). Thus, the precise correlation between the increase of the Krebs cycle and oxidative phosphorylation and the total mitochondrial proteins in the slow muscle suggests that the differences between the muscle types in oxidative metabolism are not a result of specific composition of the mitochondria but came only from different amount of mitochondria in various types of fibers.

Fatty Acid Metabolism

Beside carbohydrates, free fatty acids (FFA) are another important source of energy. Our proteomic analysis allowed monitoring of the titers of all major components of the metabolism of FFAs, including the cytoplasmic transporters (Fabp), acetyl-coenzyme A synthetase (Acsl1), the carnitine shuttle, and the enzymes involved in β-oxidation (Figure 6A). On average, in the slow-twitch muscle the titers were at least 3 times higher than those in the fast-twitch muscle. Notably, in slow muscle the titers of many proteins involved in FFA catabolism are at similar levels as those of the abundant glycolytic enzymes (Figure 3A and Figure 5A). This may suggests the importance of FFA breakdown and its significance I



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CONCLUSIONS

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ASSOCIATED CONTENT

S Supporting Information *

Proteins of the contractile machinery constitute more than 50% of the total protein in the muscle. Presence of these highly abundant proteins in muscle lysates have been a critical obstacle in proteomic analysis of this tissue. So far, only few studies, involving extensive sample fractionation and relative SILAClabeling-based protein quantitation, were able to provide deeper insights in the proteomes of the mouse skeletal muscles.10,64 Even in these proteomic efforts, the quantitative protein composition of the skeletal muscle fibers remained poorly characterized. In this study, we analyzed isolated slow and fast muscles using consecutive protein digestion (MED FASP) and standard LC−MS/MS. This relatively simple experimental approach allowed identification of about 2000 proteins per sample. The proteins were quantified by means of the Total Protein Approach providing protein concentration estimates.17 The created data set offers a comprehensive quantitative picture of the protein composition of the slow and fast muscles (Figure 7). Such global quantitative insight into metabolic proteins allows for physiological speculations and reinterpretation of ideas on the functioning of individual types of skeletal muscles. For example, our results strongly suggest that the activation of Pfk, and hence glycolysis, by F2,6P2, the product of Pfkfb1, is not a feature of the white muscle but the red one. This is unexpected because just the white muscle is known from its ability to rapid and large acceleration of glycolysis. Evidently, the crucial role in the activation of glycolysis in the white muscle play the calcium/calmodulin-dependent protein kinases like Camk2, whereas Pfkfb1 plays only the minor role. Our analysis suggests that the white muscles developed the mechanism of keeping the F2,6P2 concentration on the possible lowest level: the concentration of TIGAR, a protein which hydrolyses F2,6P2, is much higher in the white than in the red muscle. F2,6P2 is not only an activator of glycolysis but it is also a potent inhibitor of Fbp2, a regulatory enzyme of glyconeogenesis. Thus, the low titer of Pfkfb1 and the high of TIGAR suggests that the white muscles are fitted to glycogen synthesis from carbohydrate precursors. And indeed, we found that the concentration of Fbp2 was about three times higher in the white muscle. In contrary to the procedures involved in traditional enzyme activity assays, the sample preparation of method used in our proteomics study is robust, more accurate and fast. It also allows complete extraction of proteins from subcellular structures. Additionally, the samples preparation method used here protects the proteins against degradation by subcellular proteases and essentially bypasses the obstacles such as reversible dissociation and posttranslational modifications of the enzymes. Finally our method provides biggest advantage over traditional enzymatic assays by providing titers of hundreds of enzymes simultaneously and in relatively short period of time. In conclusion, this work provides for the first time a comprehensive quantitative analysis of white and red muscle. Although our data set covers only a part of the entire skeletal muscle proteome, we show that quantification of more than 1000 proteins is sufficient to study all the basic metabolism pathways of this tissue. Future analyses using newer mass spectrometers that are faster and more sensitive will allow monitoring of the titers of low abundant proteins such as specific transcription factors and receptors.

Supplementary Table 1, list of the identified peptides; Supplementary Table 2, list of the identified proteins; Supplementary Table 3,. summary of the selected protein classes and Gene Ontology categories. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Address: Department of Proteomics and Signal Transduction, Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, D82152 Martinsried, Germany. Tel.: +49 89 8578 2502. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank Dr. Matthias Mann for continuous support, Katharina Zettl for technical assistance and Korbinian Mayr for support in mass spectrometric analysis. This work was supported by the Max-Planck Society for the Advancement of Science and the Polish National Center of Science (DEC-2011/ 01/N/NZ5/04253) and Polish Ministry of Science and Higher Education (Contract Grant Number: N N401 376139).

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ABBREVIATIONS: Acaa2, 3-ketoacyl-CoA thiolase; Acadl, long-chain specific acylCoA dehydrogenase; Acadm, medium-chain specific acyl-CoA dehydrogenase; Acads, short-chain specific acyl-CoA dehydrogenase; Acadvl, very long-chain specific acyl-CoA dehydrogenase; Aco2, aconitate hydratase, mitochondrial; Acsl1, longchain-fatty-acid−CoA ligase 1; Ak1, adenylate kinase isoenzyme 1; Aldoa, fructose-bisphosphate aldolase A; Ampd1, AMP deaminase 1; Ckm, creatine kinase M-type; Ckmt2, creatine kinase S-type; Cpt1b, carnitine O-palmitoyltransferase 1; Cpt2, carnitine O-palmitoyltransferase 2, mitochondrial; Cs, citrate synthase; Dlat, dihydrolipoyllysine-residue acetyltransferase component of pyruvate dehydrogenase complex; Dld, dihydrolipoyl dehydrogenase, mitochondrial; Echs1, enoyl-CoA hydratase; Eno3, β-enolase; F2,6P2, fructose 2,6-bisphosphate; FASP, filter aided sample preparation; Fbp, fructose-1,6bisphosphatase; Fh, fumarate hydratase; Gapdh, glyceraldehyde-3-phosphate dehydrogenase; Got1, aspartate aminotransferase; Got2, aspartate aminotransferase; Gpd1, glycerol3-phosphate dehydrogenase; Gpd2, glycerol-3-phosphate dehydrogenase; Gpi, glucose-6-phosphate isomerase; Gsr, glutathione reductase; Gys, glycogen synthase; Hadh, hydroxyacylcoenzyme A dehydrogenase; Hadha, trifunctional enzyme subunit α; Hadhb, trifunctional enzyme subunit β; Hk2, hexokinase-2; Idh2, isocitrate dehydrogenase; Idh3a, isocitrate dehydrogenase subunit α; Idh3b, isocitrate dehydrogenase subunit β; Ldha, L-lactate dehydrogenase A; Ldhb, L-lactate dehydrogenase B; Mb, myoglobin; Mdh1, malate dehydrogenase 1; Mdh2, malate dehydrogenase 2; MED-FASP, multienzyme digestion-FASP; Myh1, myosin-1; Myh2, myosin-2; Myh4, myosin-4; Myh7, myosin-7; Ogdh, 2-oxoglutarate dehydrogenase; Pc, pyruvate carboxylase; Pdha1, pyruvate dehydrogenase E1 component subunit α; Pdhb, pyruvate dehydrogenase E1 component subunit β; Pdhx, pyruvate dehydrogenase protein X component; Pdk1, 2, and 4, pyruvate J


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dehydrogenase kinase isozymes 1, 2, and 4; Pfm, muscle 6phosphofructokinase; Pgam2, phosphoglycerate mutase 2; Pgd, 6-phosphogluconate dehydrogenase; Pgk1, phosphoglycerate kinase 1; Pgls, 6-phosphogluconolactonase; Pgm1, phosphoglucomutase-1; Pkm1, pyruvate kinase isozymes M1 Pkm1/2; PPP, pentose phosphate pathway; Pygm, glycogen phosphorylase, muscle form; Slc25a20, carnitine/acylcarnitine carrier protein; Slc2a4, solute carrier family 2, Glut4; Sucla2, succinylCoA ligase [ADP-forming] subunit β; Suclg1, succinyl-CoA ligase [ADP/GDP-forming] subunit α; Sdh, succinate dehydrogenase; Taldo1, transaldolase; Tigar, probable fructose-2,6bisphosphatase; Tkt, transketolase; Tpi, triosephosphate isomerase

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Absolute Quantitative Profiling of the Key Metabolic Pathways in Slow

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