Comprehensive Proteomic and Metabolomic Profiling of Soleus Muscle of Rats Exposed to Hindlimb Unloading Reveals Changes Related to Muscle Atrophy

doi:10.21203/rs.3.rs-4893443/v1

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Comprehensive Proteomic and Metabolomic Profiling of Soleus Muscle of Rats Exposed to Hindlimb Unloading Reveals Changes Related to Muscle Atrophy

https://doi.org/10.21203/rs.3.rs-4893443/v1

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Background

Skeletal muscle atrophy, which is induced by factors such as disuse, spaceflight, certain medications, neurological disorders and malnutrition, is a global health issue with clinical manifestations mainly being a reduction in muscle mass and muscle weakness. Currently there is a lack of effective treatment for muscle atrophy. Hindlimb unloading is currently a commonly used model for muscle atrophy. However, the underlying mechanism of muscle atrophy induced by hindlimb unloading remains unclear, particular from the perspective of myocyte proteome and metabolism.

Methods

We first conducted proteomic sequencing based on mass spectrometry to explore the protein abundance changes of soleus muscles from rats exposed to hindlimb unloading. Then untargeted metabolomics analysis was performed, followed by the combined analysis of proteomic and metabolomic profiles.

Results

In our study, 1052 differentially expressed proteins and 377 differentially abundant metabolites were revealed in HU group compared to CON group. These differentially expressed proteins included some proteins which are mainly expressed in the fast-twitch muscle such as ACTN3, MYH4, MYBPC2 and MYOZ1. Some metabolism-related proteins such as GLUL, GSTM4 and NDUFS4 were screened out. Some differentially abundant metabolites including arachidylcarnitine and 7,8-dihydrobiopterin, along with pathways such as histidine metabolism, taurine and hypotaurine metabolism might be related to muscle atrophy. Protein and metabolism joint analysis revealed that some pathways such as glutathione metabolism, ferroptosis and lysosome pathways were likely to be involved in soleus atrophy.

Conclusion

In this study, we have applied integrated deep proteomic and metabolomic analysis. The upregulation of proteins which are expressed in fast-twitch fibers indicated the conversion of slow-twitch fibers to fast-twitch fibers under HU. Some metabolism-related proteins have been screened out. Besides, some differentially abundant metabolites and pathways revealed the important role of metabolism in the muscle atrophy of soleus. Our study provides insights into the pathogenesis and treatment of muscle atrophy that results from unloading by integrating the proteomics and metabolomics of soleus muscles.

Muscle atrophy

Hindlimb unloading

Proteomics

Metabolomics

Integrated analysis

Skeletal muscle atrophy caused by mechanical unloading leads to a decline in physical strength and an increased risk of disability. Understanding the underlying processes is essential for developing strategies to combat this type of muscle deterioration. The disuse and unloading of muscles are likely the most significant factors that mediate spaceflight-induced muscle atrophy and have been extensively studied and reviewed. Skeletal muscle is a multicellular tissue consisting of myofibers, which accounts for approximately 40% of the overall weight of the human body and is key to exercise and energy metabolism. Depending on the expression of myosin heavy-chain isoform as well as the metabolic and contractile properties, skeletal muscle fibers are classified into following three main types: type I (slow oxidative), type IIa (fast oxidative), and type IIb (fast glycolytic)[1]. Unloading leads to a distinctive decline in the mass of the antigravity muscles, especially soleus, which are abundant in slow-twitch type I fibers, which is confirmed in human bed rest studies and in tail-suspension rat models[2]. There are some proteomic studies related to muscle atrophy during mechanical unloading due to real spaceflight or bed rest[3, 4]. However, single omics can hardly provide a comprehensive biological perspective.

Apart from reduction in muscle mass and volume, muscle atrophy also involves complex metabolic changes within muscle cells, such as an imbalance between protein synthesis and degradation, and alterations in metabolic pathways [1]. Previous studies have found that the metabolic properties of muscle fibers have been modified during unloading. After 3 weeks of unloading, the muscles of rats show fuel uptake shift from fatty acid towards glucose[5]. Furthermore, studies have indicated the increase of triglycerides in atrophic muscles, along with changes in phospholipids during atrophy[6]. Although a number of metabolite levels have been shown to be altered in unloading induced skeletal muscle atrophy, the application of metabolomics and proteomics joint analysis to investigate the mechanisms is rare.

To the best of our knowledge, this is the first study to combine the proteomics and metabolomics to investigate soleus muscle atrophy induced by unloading. For this purpose, we used hindlimb unloading models on adult rats for up to 28 days to achieve an unloading effect. Analyzing changes in both proteins and metabolites simultaneously can help to identify key biomarkers more accurately in the future, understand the molecular mechanisms behind muscle atrophy and potentially discover new therapeutic targets.

Animal

Male Sprague-Dawley rats were sourced from the Experimental Animal Facility at the Air Force Medical University in China. Conducted ethically, all procedures involving animals adhered to the protocols approved by the Institutional Animal Care and Use Committee of the same institution (Approval code: 20210325). The specific number of animals utilized for each study is illustrated in the corresponding figure legends. The animals were assigned into two groups: the control group (CON) and the hindlimb unloading group (HU). The hindlimb unloading model is well-established for simulating microgravity-induced cephalad fluid shift and cardiovascular deconditioning[7]. Two-month-old Sprague-Dawley rats in the HU group were subjected to a sustained − 30° head-down tilt with their hindlimbs unloaded for 28 days to simulate the effects of microgravity. The CON group received identical handling, excepting tail suspension.

Soleus isolation

After administering pentobarbital sodium intraperitoneally at a dosage of 50 mg/kg, the animals were euthanized via abdominal aortic exsanguination. Then, the rats were positioned in a supine orientation for surgical procedures. Bilateral soleus muscles were meticulously excised, rinsed exhaustively with phosphate-buffered saline to remove residual blood and debris, and subsequently weighed. The right soleus muscle was promptly immersed in liquid nitrogen for freezing and then transferred to a -80°C freezer after 15 minutes; the left soleus muscle was immersed in 10% neutral formalin for subsequent embedding.

Histological analysis

Following paraffin embedding, the tissue specimens were sectioned into thin microtome slices. Subsequently, the muscle sections were subjected to Haematoxylin–eosin staining (HE) staining. In preparation for Immunofluorescence analysis, the muscle sections were first blocked with 5% Bovine Serum Albumin solution for one hour. Then, the sections were incubated with primary antibodies targeting alpha-actinin 3 (ACTN3), Glutamine Synthetase (GLUL), Glutathione S-transferase M4 (GSTM4), Fructose-1,6-bisphosphatase isozyme 2 (FBP2), Yes-associated protein 1 (YAP1), and NADH dehydrogenase iron-sulfur protein 4 (NDUFS4) overnight at 4°C. Each primary antibody was applied at a dilution of 1:200 (Proteintech, China). Afterward, the secondary antibody was incubated for 1 hour at room temperature. The images were captured using a CaseViewer 2.4 imaging system.

Proteomics analysis

Proteins from muscle tissue samples were extracted from both the control and the HU groups. Utilizing RIPA-lysis buffer, the extraction was executed on a cohort of three mice per group. The samples adhered to the filter-aided sample preparation methodology as per the manufacturer's guidelines. Proteins underwent enzymatic digestion with trypsin, applied at a ratio of 50:1 to protein. Centrifugation was used to collect peptide samples for proteomic analysis followed by reconstituted peptides in sample loading buffer. Peptides were solubilized in solvent A and directly loaded onto a bespoke reversed-phase analytical column (25 cm × 100 µm i.d.). The chromatographic separation employed a binary solvent system: solvent A (0.1% formic acid, 2% acetonitrile in water) and solvent B (0.1% formic acid, 90% acetonitrile in water). A gradient elution was applied (0-22.5 min, 6%-22% B; 22.5–26.5 min, 22%-34% B; 26.5–28.5 min, 34%-80% B; 28.5–30 min, 80% B) at a flow rate of 700 nl/min on an EASY-nLC 1200 UPLC system. The peptides were then subjected to nano-electrospray ionization followed by analysis on an Orbitrap Exploris 480 mass spectrometer. The FAIMS CV was set to 45 V, and the electrospray voltage was 2300 V. The Orbitrap was configured to record precursor ions and their fragments within a 350–1400 m/z range at a resolution of 60000 for full MS scans and 15000 for MS/MS scans, with an HCD NCE set at 27%. The automatic gain control target was fixed at 1E6, and the maximum injection time was set to 22 ms. We constructed a Spectral Library using DDA data processed with Spectronaut v.17.0 and the Pulsar search engine, comparing tandem mass spectra to the Homo_sapiens_9606_ SP_ 20230103. fasta database (20389 entries) with concatenated decoy sequences. The maximum allowed missed cleavages was set to 2, with 1% FDR adjustments for PSMs, peptides, and proteins. The spectral library was then imported into Spectronaut for retention time prediction using nonlinear correction and cross-referenced with DIA data. PPI analysis was performed using the STRING database (https://string-db.org/) and Cytoscape software (version 3.8.1).

Western blot analysis

The total tissue samples underwent separation via a 10% SDS-PAGE gel electrophoresis process and then transferred onto a 0.45-µm polyvinylidene fluoride membrane. The membranes were blocked with 5% non-fat milk in Tris-buffered saline with Tween 20 for 2h at room temperature. The membranes were then incubated with antibodies against ACTN3 (Proteintech, 1:2000), GLUL (Proteintech, 1:4000), GSTM4 (Proteintech, 1:2000), FBP2 (Proteintech, 1:2000), YAP1 (Proteintech, 1:5000), NDUFS4 (Proteintech, 1:2000) and GAPDH (Zhuangzhi, 1:2000) allowing for an overnight incubation at 4°C. GAPDH were used as protein loading control. Secondary antibody was either anti-mouse or anti-rabbit secondary antibody. Protein bands were visualized by an enhanced chemiluminescence (Millipore). The band intensities were analyzed by ImageJ.

Metabolomics Analysis

Muscle samples were stored in a -80°C low-temperature freezer. Samples were transferred to EP tubes, and extraction solution containing isotopically labeled internal standards was added. After vortex mixing for 30 seconds followed by sonication, the samples were left to stand at -40°C for 1 hour. After centrifugation for 15 minutes, the supernatant was collected and placed in injection vials for machine detection. An equal amount of supernatant from all samples was mixed to form a quality control sample, which was also analyzed on the machine. In this project, a Vanquish (Thermo Fisher Scientific) ultra-high-performance liquid chromatograph was used, with the Waters ACQUITY UPLC BEH Amide liquid chromatography column employed for chromatographic separation of target compounds. The liquid chromatography mobile phase A was the aqueous phase, and phase B was acetonitrile. The sample tray temperature was set to 4°C, with an injection volume of 2 µL. The Orbitrap Exploris 120 mass spectrometer was used to collect both first-order and second-order mass spectrometry data under the control of the Xcalibur 4.4 software (Thermo). Detailed parameters are as follows: Sheath gas flow rate: 50 Arb, Aux gas flow rate: 15 Arb, Capillary temperature: 320°C, Spray Voltage: 3.8 kV for positive mode or -3.4 kV for negative mode. The raw data, after being converted to mzXML format using the ProteoWizard software, was processed for metabolite identification using a custom R package, with the BiotreeDB (V3.0) database utilized for this purpose. Subsequently, a self-developed R package was used for visualization analysis.

Statistical analysis

Data analysis was conducted using GraphPad Prism software. The results are presented as the mean ± SEM of three independent experiments. Comparisons were analyzed by an unpaired t-test. A p-value < 0.05 is considered as statistically significant

1. Soleus muscle atrophy induced by hindlimb unloading

The hindlimb-unloading rat model is a typical model commonly used for weightlessness-induced muscle atrophy (Fig. 1A). In this study, we found that HU for 28 days did not affect adult rats’ body mass (Fig. 1B), which is similar to the results of previous studies[8]. Nevertheless, soleus muscles of rats showed decreases in all dimensions in the HU group in comparison with CON group. As a result of unloading, soleus mass (Fig. 1C) and soleus/body mass (Fig. 1D) were lower in the HU group compared to the control group. According to HE staining, the mean fiber cross section area of soleus was smaller after HU (Fig. 1E). In conclusion, HU could induce soleus atrophy in rats exposed to hindlimb weightlessness for 28 days.

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Figure.1 Analysis of soleus muscle atrophy induced by hindlimb unloading (n = 6). A, The model of Hindlimb Unlaoding in rats. B, Body mass collected at CON group (CON), Hindlimb Unloading (HU). C, Wet soleus mass and Soleus/Body Mass(D). E, Myofibre cross-sectional area (CSA) of soleus. (Scale Bar = 50µm.The data represent the mean ± SEM, n = 3; ***P < 0.001, ****P < 0.0001)

2. Proteomic changes in soleus of rats after HU

We used the tandem mass tag mass spectrometry method to analyze soleus tissue samples from the CON group and the HU group, which allowed us to comprehensively elucidate the proteomic regulation of muscle atrophy. In order to evaluate the repeatability of muscle samples, Principal components analysis (PCA) was performed on all samples. According to PCA, samples were clustered mainly by tissue of origin (Fig. 2A). After the process of data filtering, a total of 4668 proteins were successfully identified, out of which 4495 proteins were quantified for the purpose of comparison (Fig. S1). We set the threshold for significant upregulation to be fold change(FC) > 1.5 (P < 0.05) and the threshold for significant downregulation to be fold change<1/1.5 (P < 0.05). As a result, 1052 DEPs were found in HU group compared to the CON group, with 787 up-regulated and 265 down-regulated (Fig.S2). The heatmap showed the clustering relationship of the relative expression of Differentially Expressed Proteins (DEPs) (Fig. 2B). Subcellular localization analysis revealed that the largest number of entities were cytoplasmic, followed by nuclear and extracellular (Fig. 2C).

Gene Ontology (GO) enrichment analysis (Fig. 2D) and KEGG analysis (Fig.S3) for DEPs were performed. A total of 45 GO categories were classified, with DEPs being enriched in biological processes, cellular components and molecular functions. The majority of enriched categories in cellular component were intracellular anatomical structure and cytoplasm. Apparently, the vast majority of biological processes terms were relevant to metabolic process, such as organic substance metabolic processes, cellular metabolic processes, primary metabolic processes (Fig. 2D), suggesting that these processes played an important role in soleus muscle atrophy induced by unloading. For molecular function, 15 GO terms were enriched, among which protein binding and ion binding were dominant. KEGG analysis revealed that vitamin digestion and absorption, complement and coagulation cascades, cholesterol metabolism were enriched pathways. In addition, DEPs were also enriched in glycolysis/glyconeogenesis and protein digestion and absorption according to KEGG pathway analysis. This result was consistent with previous report that glucose oxidation was increased in unloaded muscle [5] and the notion that atrophic state is attributed to the enhanced proteolysis and compromised protein synthesis. Then the PPI network of top 25 upregulated and top 25 downregulated DEPs was constructed to filter out the key gene involved in muscle atrophy (Fig. 2F). Eight hub genes, including ANKRD2, ATP2A1, TTN, MYL2, MYBPC2, ACTN3, MYH4, MYH3, were acquired by taking the overlap among MCC, MNC and Degree.

Figure. 2 Proteomic analysis between the HU group and the CON group (n = 3). A, PCA analysis of HU and CON groups. The horizontal and vertical axes show the degree of interpretation of PC1 and PC2, with higher values increasing the degree of interpretation. The degree of aggregation within groups represents the repeatability of the grouped samples, and the repeated samples in each group tend to be clustered together. B, Heatmap of hierarchical clustering analysis for all groups. The horizontal coordinate represents the grouping of different samples. Red indicates the high expression of the substance, and blue indicates the low expression of the substance. C, Pie plot showing the different classifications of DMPs. Different color blocks indicate different taxonomic categories, and percentages indicate the proportion of proteins belonging to that type among all identified proteins percentage of the number. D, GO classification shows the DEPs classification. The horizontal axis represents the number of differentially expressed proteins in the classification, and the vertical axis represents the secondary functional classification in the primary classification of GO (Biological process/Cellular component/Molecular function). The figure shows the first-order classification of GO in different colors. E, KEGG analysis of DEPs. The dotplot shows the 20 most significantly enriched functions. The vertical axis represents the KEGG function description information, while the horizontal axis represents the enrichment significance P value of -Log10 transformation, and the higher the value represents the stronger the enrichment significance. F, Protein–protein interaction (PPI) network of DEGs between HU and CON based on the STRING database. Red nodes indicate upregulated proteins, and green represents downregulated proteins.

3. Proteomic analysis revealing DEPs related to unloading muscle atrophy

Proteins were selected for further analysis based on both their high fold change and their probable role in muscle atrophy according to the proteomic data (Fig. 3A). The increased expression of MYH4, ACTN3, myozenin 1 (MYOZ1), a structural protein involved in muscle regeneration[9], and myosin binding protein C (MYBPC2) indicated the increased proportion of fast-twitch fibers in unloaded soleus because these four proteins are mainly expressed in fast-twitch muscle fibers[10, 11]. This result was consistent with previous studies that gravitational unloading leads to the transformation of slow-twitch muscle fibers into fast-twitch fibers[12]. Similarly, ATPase sarcoplasmic/endoplasmic reticulum Ca2 + transporting 1 (ATP2A1), which is also known as the sarco (endo) plasmic reticulum Ca²⁺ ATPase type 1 (SERCA1) and expressed in fast-twitch muscles[13], was upregulated in unloaded soleus. The decreased expression of myozenin 2 (MYOZ2), which is specifically expressed in slow skeletal muscle fibers[14] further proved the shift from slow-twitch muscle fibers into fast-twitch fibers. Additionally, the muscle contraction-related troponin family member troponin C2 (TNNC2), which was expressed in fast-twitch fibers[15], was upregulated, whereas Troponin I1 (TNNI1) and Troponin C1 (TNNC1), expressed in slow skeletal muscle fibers[16, 17], were downregulated in soleus of unloading rats. The decreased expression of YAP1, a key effector of the Hippo pathway and a key regulatory factor involved in skeletal muscle development and regeneration[18], was shown in this study.

In addition to muscle contraction-related structural protein, it is worth noting that several proteins involved in metabolic processes were dysregulated in unloaded soleus of rats. The expression of GLUL, the only enzyme capable of synthesizing glutamine, was increased after hindlimb unloading. According to our proteomics analysis, glutathione transferase family members A3, P1, T3, M1, M3, M4 (GSTA3, GSTP1, GSTT3, GSTM1, GSTM3, GSTM4), which are located in the cytoplasm of both cardiac and skeletal muscle[19], were upregulated. FBP2 is a muscle-specific form of fructose bisphosphatase that converts fructose-1,6-bisphosphate to fructose-6-phosphate in mammalian muscle, which was abundant in fast-twitch muscle tissue. Similarly to previous findings in mouse[20], the expression of FBP2 was increased in response to gravity unloading in soleus muscle of rats. NDUFS4 plays a crucial role in mitochondrial energy metabolism, which was also downregulated after hindlimb unloading. Additionally, the protein expression of several other NADH dehydrogenases, including NADH:ubiquinone oxidoreductase subunit S6-like 1(NDUFS6L1) and NADH:Ubiquinone Oxidoreductase Subunit A7(NDUFA7), was also decreased after hindlimb unloading. Consistent with our data from proteomics analysis, western blot results indicated that the expression of ACTN3, GLUL, GSTM4 and FBP2 was upregulated, and the protein levels of NDUFS4 and YAP1 were decreased in unloading muscles (Fig. 3B). The expression of ACTN3, GLUL, GSTM4, FBP2, YAP1 and NDUFS4 was also verified by immunofluorescence (Fig. 3C). Based on these changes in representative proteins, we can gain a better understanding of disuse muscle atrophy induced by hindlimb unloading.

4. Metabolic analysis revealing metabolites changes of soleus in response to unloading

Because metabolites such as glucose, lipid and triglycerides are potential modulators of muscle atrophy[21, 22], we used LC-MS/MS metabolomic analysis to investigate the role of metabolites in soleus after unloading. Before conducting a detailed analysis of specific metabolic alterations, we applied OPLS-DA model to preliminarily evaluate metabolic differences between HU group and CON group (Fig. 4A). The permutation histogram test of OPLS-DA model showed that a clear separation between the HU group and the CON group, suggesting reproducible chemical differences.

Following a preliminary observation of the disparities, we employed both univariate and multivariate statistical methods to identify the distinct metabolites in the soleus. Based on the screening criteria P < 0.05, Variable Importance in the Projection (VIP) > 1 and FC > 1.5 or FC < 0.67 in this study, a total of 4285 differentially abundant metabolites (DAMs) were identified, of which 1754 DAMs were upregulated and 2531 DAMs were downregulated. Among these DAMs, 377 had a member signature (MS2) name provided by the mass spectrometry qualitative matching analysis (Fig. 4B). According to chemical classification information, DAMs were classified into 23 types, and the proportions of each type of metabolite were shown (Fig. 4C). Among the 377 metabolites, organ heterocyclic compounds accounted for the highest proportion, accounting for 17.37%, followed by lipid and lipids-like molecules, accounting for 15.7%. The top 20 most significantly changed metabolites were displayed in Fig. 4D, with these metabolites primarily concentrated in the pathways of amino acid metabolism and lipid metabolism. The top 5 upregulated metabolites were arachidyl carnitine, 7,8-dihydrobiopterin, asn-gly-asn, thr-leu and ser-leu, and the top 5 downregulated metabolites were diallyl trisulfide, 5-(4-morpholinylsulfonyl)-1h-indole-2,3-dione, phenamil, 5-[3-(trifluoromethyl)phenyl] furfural and epigallocatechin. Then we performed KEGG enrichment analysis on DAMs to better understand metabolic pathways (Fig. 4E). According to KEGG analysis, 108 metabolic pathways have been classified and annotated. The top 10 significantly enriched KEGG metabolic pathways according to differential abundance score were biosynthesis of amino acids, glycerophospholipid metabolism, d-amino acid metabolism, ABC transporters, histidine metabolism, central carbon metabolism in cancer, alanine, aspartate and glutamate metabolism, protein digestion and absorption, aminoacyl-tRNA biosynthesis and choline metabolism in cancer (Fig. 4E). Notably, the protein digestion and absorption pathway were co-enriched in proteomics and metabolomics, suggesting the pivotal role of this pathway in muscle atrophy induced by unloading. Additionally, pathway analysis by MetaboAnalyst was performed. The results showed that these DAMs were significantly enriched in pathways including alanine, aspartate and glutamate metabolism, D-glutamine and D-glutamate metabolism, arginine and proline metabolism, histidine metabolism, taurine and hypotaurine metabolism (Fig. 4F). It was noteworthy that histidine metabolism and alanine, aspartate and glutamate metabolism were enriched in both KEGG analysis and pathway analysis by MetaboAnalyst, indicating their important role in soleus atrophy.

5. Correlation Analysis of Proteomics and Metabolomics

In order to clarify the mechanism contributing to soleus atrophy caused by HU, we performed an integrated proteomic-metabolomic analysis. There were 45 and 108 KEGG pathways specifically enriched in proteomics and metabolomics, respectively (Fig. 5A, B), from which we screened out 16 common pathways including purine metabolism, protein digestion and absorption, lysosome, glucagon signaling pathway, glutathione metabolism and ferroptosis. Figure 5C and D showed the KEGG pathway maps of lysosome and ferroptosis. Some lysosomal acid hydrolases and lysosomal membrane proteins were upregulated, indicating the enhanced hydrolytic function of lysosomes, which may be responsible for the muscle atrophy. According to pathway map of ferroptosis, the amount of glutathione disulfide (GSSG) was decreased, which may be due to the decreased activity of GPX4. Besides, the upregulation of FERRITIN, STEAP3 and NOX2 indicated the possibility of iron overload and oxidative stress occurrence. Glucagon signaling pathway map showed the decreased amount of malate and 2-oxoglutarate in citrate cycle and increased expression of LDH. (Fig.S4).

Then we conducted a correlation analysis between the 6 DEPs that we verified and all DAMs between HU and CON(Fig. 5E). The metabolites that were correlated with these 6 proteins, containing lipid-like molecules, animo acid and intermediates of the tricarboxylic acid cycle. Notably, GLUL as a glutamine synthetase exhibited a significant negative correlation with glutamine. ACTN3, FBP2 and GSTM4 were positively correlated with some dipeptides such as Ile-Leu and Hly-His. There was a significant positive correlation between NDUFS4 and malic acid. The majority of metabolites which were significantly negatively correlated with GSTM4 belonged to amino acids. YAP1 exhibited a significant positive correlation with tiglylcarnitine, a short-chain acylcarnitine.

Skeletal muscle atrophy induced by spaceflight leads to functional deficits such as decrease in maximum force generation, increased fatigability and higher activation threshold, affecting the physical function and work efficiency of astronauts. Even short-term spaceflight can result in significant muscle atrophy, with the most significant atrophy in antigravity muscles such as the soleus, even when exercise countermeasures are taken. Muscle atrophy induced by spaceflight and muscle atrophy due to aging or disuse from injury exhibit similar manifestations and may share some common underlying mechanisms. It has been shown that skeletal muscle atrophy under spaceflight conditions is accompanied by metabolic changes, including deficiency in vitamin D and decreased citrate synthesis in muscle tissue[23]. This study conducted a joint analysis of proteomics and metabolomics for the first time on the atrophy of the soleus muscle induced by hindlimb unloading. The present findings contribute to a better understanding of the spatiotemporal molecular adaptation of skeletal muscle to spaceflight and provide a large-scale database for the design of effective countermeasure protocols.

We first focused on the DEPs of soleus muscle between CON and HU group. A series of proteins that are expressed in fast muscle fibers showed a significant upregulation in their levels, such as MYH4, ACTN3, MYOZ1, MYBPC2, ATP2A1 and TNNC2. According to previous study, accumulation of ACTN3 alters type II glycolytic myofibers, subsequent accelerating age-associated muscle atrophy. Furthermore, reduction of ACTN3 expression ameliorated muscle atrophy[24]. In our study, we speculated that upregulation of ACTN3 might be key to muscle atrophy induced by unloading. Meanwhile, some proteins that are exclusively expressed in slow muscle fibers were significantly downregulated such as TNNI1, TNNC1 and MYOZ2. In addition, some differentially expressed metabolic proteins have also confirmed previous studies which indicate that simulated weightlessness causes a transition from slow muscle fibers to fast muscle fibers^[12], thereby reducing muscle endurance. The NADH dehydrogenases NDUFS4, NDUFS6L1 and NDUFA7, which play a key role in the process of oxidative phosphorylation, were downregulated. FBP2, which is reported to inhibit mitochondrial biogenesis[25], was upregulated in our study. This result is consistent with the metabolic characteristics of suppressed mitochondrial synthesis and oxidative phosphorylation in fast muscle fibers[26]. Our results indicate that FBP2 may be a key molecule in controlling the number of mitochondria during the transition from slow muscle to fast muscle. As a conditional essential amino acid during catabolic states, glutamine prevents glucocorticoids-induced muscle atrophy in rats[27]. We speculated that the increased expression of glutamine synthetase GLUL may be a compensation and negative feedback response to muscle atrophy. Besides, YAP1 has emerged as an important player in mechanotransduction, transmitting mechanical cues into a transcriptional cell response [18]. Although previous study found the pivotal role of YAP1 in regulating skeletal muscle size[28], there are no research about the change of protein level of YAP1 in response to skeletal muscle unloading. Our study for the first time finds that YAP1 expression dramatically decreased after 28 days of hindlimb unloading. The role of YAP1 in muscle atrophy caused by unloading remains to be further investigated.

The KEGG pathway enrichment analysis for DEPs has identified that the pathways for vitamin digestion and assimilation, the cascades of complement and coagulation, and the metabolism of cholesterol are notably enriched. Previous studies have reported that vitamin C enhances muscle repair by stimulating myoblast growth, suggesting the role of vitamin in the regeneration of skeletal muscle[29]. It has been reported that complement component 1q activates Wnt signaling pathway, thus leading to progression of muscle fibrosis via promoting fibroblast proliferation and decreasing the proliferative capacity of satellite cells[30]. Furthermore, previous study reports that proteins of the complement and coagulation of cascades were affected by bed rest unloading according to plasma proteome[31]. Our results provide direct evidence of the crucial role of the complement and coagulation of cascades in muscle atrophy. Additionally, muscle cholesterol metabolism plays an important role in the pathophysiology of Duchenne muscular dystrophy, which is the direct therapeutic targets in Duchenne muscular dystrophy[32].

Through metabolomic studies, we can gain a deeper understanding of the changes in metabolites within muscle cells during atrophy, which can help reveal the molecular mechanisms of muscle atrophy and potentially identify new therapeutic targets. Among the top 20 most significantly changed metabolites, three upregulated dipeptides containing leucine may promote muscle growth and repair as a feedback of soleus atrophy because leucine as an essential branched-chain amino acid enhances skeletal muscle growth[33]. The increased amount of arachidyl carnitine indicated the changes in the fatty acid oxidation process. The differential metabolite pathway enrichment analysis showed that histidine metabolism and alanine, aspartate and glutamate metabolism were enriched in both KEGG and MetabolAnalyst pathway analysis. Histidine is an important substrate for the synthesis of carnosine, which is located mainly in skeletal muscle and plays a pivotal role in the muscle contraction process through calcium regulation and pH buffering[34]. Alanine, aspartate and glutamate, which are derived from intermediates of the citric acid cycle, are closely related to the energy metabolism of soleus. Alanine catabolism in liver is reported to promote skeletal muscle atrophy in type 2 diabetes[35]. Additionally, taurine and hypotaurine metabolism pathway was enriched in MetaboAnalyst analysis. Taurine and hypotaurine metabolism play a crucial role in modulating excitation–contraction coupling in skeletal muscles and 70% of total taurine in the body is stored in skeletal muscle. Knockout of the taurine transporter in mice results in low taurine concentrations in the muscle and associates with myofiber necrosis and diminished exercise capacity. Taurine metabolism disorder is an important mechanism of Duchenne muscular dystrophy[36]. These metabolite pathways were first reported to be involved in unloading-induced muscle atrophy in our study.

The integration of proteomics and metabolomics proteomics provides a deeper understanding of the molecular mechanisms underpinning muscle atrophy. Through KEGG pathway analysis of DEPs and DAMs, we screened out 16 common KEGG pathways in which differentially expressed proteins and metabolites between CON and HU were involved, including protein digestion and absorption, ferroptosis, lysosome, glutathione metabolism and purine metabolism. The enrichment of protein digestion and absorption and the enhanced expression of some lysosome and implied that skeletal muscle atrophy occurs by an imbalance of myofibrillar protein turnover favoring protein degradation over protein synthesis. As a process of iron-dependent programmed cell death, ferroptosis pathway was also enriched. It has been found that high iron content is associated with diminished muscle mass in the elderly and in aged rats[37]. Our study indicates the iron overload and increased oxidative stress according to KEGG pathway map and first reveals that ferroptosis may be involved in disuse muscle atrophy. Additionally, glucagon signaling pathway map shows the increased expression of LDH and decreased amount of malate and 2-oxoglutarate. This finding confirms the transition from slow-twitch to fast-twitch muscle fibers in soleus exposed to unloading because fast-twitch muscle fibers rely more on glycolysis rather than oxidative phosphorylation for energy supply[38]. Although GLUL is a glutamine synthetase, glutamine was found to be negatively correlated to GLUL. This result may be due to the decreased amount of glutamate according to pathway map because glutamate is the substrate for the synthesis of glutamine. The positive correlation between YAP1 and tiglylcarnitine indicates the possible important role of YAP1 in metabolism. The role of YAP1 in metabolic pathways is increasingly recognized. YAP1 is reported to be involved in arachidonic acid metabolism in the process of liver carcinogenesis [39]. Previous studies have also confirmed the important role of YAP1 in glycolysis [40]. Our results suggest that YAP1 may play a role in the fatty acid oxidation of the soleus muscle. Besides, the amount of tiglylcarnitine, which belongs to short-chain acylcarnitine and is involved in β-oxidation of fatty acids [41], was decreased. This is consistent with the that the proportion of energy supply from fatty acid oxidation is reduced in fast muscle fibers compared with slow muscle fibers [38]. The positive correlation between NDUFS4 and malic acid is consistent with the decreased amount of malate and 2-oxoglutarate according to the above glucagon signaling pathway KEGG map, indicating the decreased activity of the tricarboxylic acid cycle in soleus muscle after unloading.

In this study, we conducted a combined analysis of proteomics and metabolomics. The analysis results confirm that unloading can lead to the transformation of slow-twitch fibers into fast-twitch fibers in the soleus muscle. Additionally, through the combined analysis of omics, we discovered some new molecules and metabolic pathways that may be involved in the process of atrophy of the soleus muscle caused by unloading such as YAP1 and ferroptosis signaling pathway. Of course, this study has some limitations, such as not verifying the levels of metabolites, not confirming changes in some pathways such as the ferroptosis pathway and the enhancement of lysosomal enzyme activity.

CON Control group

HU Hindlimb Unloading

HE Haematoxylin–eosin staining

ACTN3 Alpha-actinin 3

GLUL Glutamine Synthetase

GSTM4 Glutathione S-transferase M4

FBP2 Fructose-1,6-bisphosphatase isozyme 2

YAP1 Yes-associated protein 1

NDUFS4 NADH dehydrogenase iron-sulfur protein 4

PCA Principal Component Analysis

FC Fold Change

DEPs Differentially Expressed Proteins

GO Gene Ontology

MYOZ1 Myozenin 1

MYBPC2 Myosin binding protein C

ATP2A1 ATPase sarcoplasmic/endoplasmic reticulum Ca²⁺ transporting1

MYOZ2 Myozenin 2

TNNC2 Troponin C2

TNNI1 Troponin I1

TNNC1 Troponin C1

NDUFS6L1 NADH: ubiquinone oxidoreductase subunit S6-like 1

NDUFA7 NADH: Ubiquinone Oxidoreductase Subunit A7

VIP Importance in the Projection

DAMs Differentially Abundant Metabolites

GSSG Glutathione Disulfide

Acknowledgements

Not applicable

Author contributions

C-F L and Y W designed the study, performed the majority of the experiments, collected data and analyzed the data and wrote the manuscript. X L, Y W and N L performed experiments, collected data and approved the manuscript. X-Q S, Y-Ch W, X-D Q contributed to the designing of the experiments and assisted in the final approval of the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (No. 32100952, No. 3207090219).

Data availability

The data sets employed for analysis in the present study are accessible from the lead researcher upon request that is deemed reasonable.

Ethics approval and consent to participate

The study protocol was approved by the Ethics Committee of the Air Force Medical University in China (Approval code: 20210325). All experimental animals operating procedures were in line with the standard of the Guide for the Care and Use of Laboratory animals published by National Institutes of Health. Efforts were made to minimize the pain of the experimental animals.

Consent for publication

Not applicable.

Competing interests

The authors confirm the absence of any conflicts of interest.

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No competing interests reported.

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Comprehensive Proteomic and Metabolomic Profiling of Soleus Muscle of Rats Exposed to Hindlimb Unloading Reveals Changes Related to Muscle Atrophy

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Materials and Methods

Animal

Soleus isolation

Histological analysis

Proteomics analysis

Western blot analysis

Metabolomics Analysis

Statistical analysis

Results

1. Soleus muscle atrophy induced by hindlimb unloading

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2. Proteomic changes in soleus of rats after HU

3. Proteomic analysis revealing DEPs related to unloading muscle atrophy

4. Metabolic analysis revealing metabolites changes of soleus in response to unloading

5. Correlation Analysis of Proteomics and Metabolomics

Discussion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1