Cellular Proteome Dynamics during Differentiation ... - ACS Publications

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Cellular Proteome Dynamics during Differentiation of Human Primary Myoblasts Marie-Catherine Le Bihan,† Inigo Barrio-Hernandez,† Tenna Pavia Mortensen,† Jeanette Henningsen,† Søren Skov Jensen,† Anne Bigot,‡ Blagoy Blagoev,† Gillian Butler-Browne,‡ and Irina Kratchmarova*,† †

Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark Center for Research in Myology, Sorbonne Universités, UPMC Univ Paris 06, INSERM UMRS975, CNRS FRE3617, 75013 Paris, France

‡

S Supporting Information *

ABSTRACT: Muscle stem cells, or satellite cells, play an important role in the maintenance and repair of muscle tissue and have the capacity to proliferate and differentiate in response to physiological or environmental changes. Although they have been extensively studied, the key regulatory steps and the complex temporal protein dynamics accompanying the differentiation of primary human muscle cells remain poorly understood. Here, we demonstrate the advantages of applying a MS-based quantitative approach, stable isotope labeling by amino acids in cell culture (SILAC), for studying human myogenesis in vitro and characterize the fine-tuned changes in protein expression underlying the dramatic phenotypic conversion of primary mononucleated human muscle cells during in vitro differentiation to form multinucleated myotubes. Using an exclusively optimized triple encoding SILAC procedure, we generated dynamic expression profiles during the course of myogenic differentiation and quantified 2240 proteins, 243 of which were regulated. These changes in protein expression occurred in sequential waves and underlined vast reprogramming in key processes governing cell fate decisions, i.e., cell cycle withdrawal, RNA metabolism, cell adhesion, proteolysis, and cytoskeletal organization. In silico transcription factor target analysis demonstrated that the observed dynamic changes in the proteome could be attributed to a cascade of transcriptional events involving key myogenic regulatory factors as well as additional regulators not yet known to act on muscle differentiation. In addition, we created of a dynamic map of the developing myofibril, providing valuable insights into the formation and maturation of the contractile apparatus in vitro. Finally, our SILAC-based quantitative approach offered the possibility to follow the expression profiles of several muscle disease-associated proteins simultaneously and therefore could be a valuable resource for future studies investigating pathogenesis of degenerative muscle disorders as well as assessing new therapeutic strategies. KEYWORDS: Cell differentiation, humans, skeletal muscle, primary cell culture, quantitative proteomics, SILAC, muscle regeneration

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INTRODUCTION

proliferative myoblasts undergo a well-characterized sequence of morphological and transcriptional changes, leading to the formation of postmitotic plurinucleated myotubes. This cellular conversion is initiated by differentially expressed myogenic regulatory transcription factors (MRFs): MyoD (MYOD1), MYF5, myogenin (MGN), and MRF4.5,6 Global gene expression patterns7,8 that coincide with these different states and transitions are providing the framework for understanding the hierarchical molecular program that coordinates the switch between muscle cell proliferation and differentiation. However, it is clear that monitoring the protein levels through temporal profiling of the proteome is necessary to complement and

Skeletal muscle accounts for about 40% of the body mass, and, in addition to being responsible for voluntary movement, it is also one of the major sources of energy. In adults, it has a very low basal rate of cellular turnover, but it retains a remarkable capacity to adapt to normal physiological demands during growth and training and to regenerate in response to injury or disease.1 This regenerative capacity relies mainly on a population of quiescent mononucleated muscle stem and precursor cells called satellite cells.2 Upon activation signals, satellite cells are recapitulating the embryonic myogenic program locally, whereby myoblasts proliferate, migrate, differentiate, and fuse together to form new plurinucleated myotubes.1,3,4 A small percentage of proliferating myoblasts do not differentiate and return to quiescence to restore the pool of satellite cells. During myogenic differentiation in vitro, © XXXX American Chemical Society

Received: May 11, 2015

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DOI: 10.1021/acs.jproteome.5b00397 J. Proteome Res. XXXX, XXX, XXX−XXX

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Journal of Proteome Research

with French legislation on ethics.27 In standard cell culture conditions, cells were expanded in growth medium (GM) (Dulbecco’s modified Eagle’s medium (DMEM; low glucose [1 g/L]) supplemented with 20% fetal bovine serum (FBS), 2 mM GlutaMAX, and 5 μg/mL gentamycin (Invitrogen, Paisley, UK)) in 5% CO2 at 37 °C in a humid atmosphere. Confluent cultures were induced to differentiate by switching them to serum-free high-glucose DMEM (i.e., 4.5 g/L glucose) supplemented with 2 mM GlutaMAX and 5 μg/mL gentamycin (differentiation medium, DM). For SILAC experiments, cells were expanded in either light, medium, or heavy GM. These SILAC labeling media consisted of custom prepared lowglucose DMEM deficient in arginine and lysine (Invitrogen) containing 20% dialyzed fetal bovine serum (dFBS), 2 mM GlutaMAX, and 5 μg/mL gentamycin (Invitrogen) supplemented with SILAC amino acids (Cambridge Isotope Laboratories and Sigma-Aldrich): L-arginine (Arg0) and Llysine (Lys0), L-lysine-2H4 (Lys4) and L-arginine-13C6 (Arg6), or L-lysine-13C6-15N2 (Lys8) and L-arginine-13C6-15N4 (Arg10) at a concentration of 28 mg/L for the arginine and 73 mg/L for the lysine amino acids.28,29 In order to replenish the dialyzed serum from growth-promoting factors, a cocktail of molecules promoting myoblast expansion was also added to SILAC GMs: 5 ng/mL EGF (PeproTech), 0.5 ng/mL bFGF (Invitrogen), 5 μg/mL insulin (Sigma-Aldrich), and 0.2 μg/mL dexamethasone (Sigma-Aldrich). Differentiation of labeled cultures was initiated by transferring them in serum-free isotope-labeled DM consisting of low-glucose DMEM lacking arginine and lysine supplemented with glucose (4.5 g/L), 2 mM GlutaMAX, and 5 μg/mL gentamycin (Invitrogen) and SILAC amino acids. For all experiments, the mean population doublings (MPD) at each passage was calculated using the following equation: ln(N/ n)/ln 2, where N is the number of cells counted and n is the number of cells initially plated.23 To ensure complete SILAC incorporation, human myoblasts were grown in labeling media for 9 doublings prior to further manipulation of the cells.

better resolve the molecular mechanisms underlying the phenotypic transition during myogenic differentiation. From cataloguing the proteome of whole muscle,9−12 and more recently characterizing individual muscle fibers,13 mass spectrometry (MS)-based proteomics have largely contributed to the myology field.14,15 Large-scale proteomic studies on rodent skeletal muscle cell lines have also provided invaluable information on the global changes affecting the proteome during in vitro muscle formation.16−19 Although mouse C2C12 and rat L6 are widely used experimental models to study myogenesis in vitro, these rodent cell lines, by nature of their immortality, may not represent bona f ide satellite cells. Additionally, as transformed cells, they are prone to genetic instability and consequently may lose tissue-specific function characteristic of their mortal parental population after longterm in vitro expansion.20 Moreover, the discrepancies observed in some murine models of muscle diseases as compared to the patients’ phenotype emphasize the need to investigate postnatal myogenesis of human satellite cells.21,22 Thus, primary cultures of human cells derived from muscle biopsies provide the most relevant experimental models to study myogenesis in vitro despite their added complexity (e.g, access to patients’ biopsies, myogenic purity, and limited proliferative capacity).23,24 Such cell culture systems are also excellent tools for dissecting the physiopathological mechanisms involved in degenerative muscle disorders as well as for developing and testing various therapeutic strategies (e.g., pharmacological, gene-based, and cell-based approaches).22 In the current study, we used primary human muscle cells to model the early stages of regeneration of muscle progenitors and applied an MS-based quantitative approach, stable isotope labeling by amino acids in cell culture (SILAC), to identify and quantitatively evaluate their dynamics expression profile during in vitro differentiation. SILAC is an extremely powerful method to evaluate in vitro protein dynamics and was first demonstrated in the study of the differentiation of the murine C2C12 skeletal muscle cell line.16 Using SILAC, the entire proteome of a given cell population is metabolically labeled by heavy, nonradioactive isotopic variants of specific amino acids.25 Thereafter, two or more distinctly SILAC-labeled cell populations can be mixed and analyzed in one MS experiment, which allows accurate quantification of proteins from the different cellular states. Here, we optimized our growth conditions in the presence of SILAC labeling medium and successfully achieved complete labeling of human primary myoblasts without altering myotube formation. Using a triple SILAC encoding strategy,26 we then followed the switch-like changes in global protein expression during the differentiation of human primary muscle cells. The resulting profiles revealed important remodeling in key cellular functions relevant to cell growth and myotube formation. Importantly, this straightforward quantitative approach offered new insights into the dynamic process of myofibril formation in vitro. Additionally, our data allowed us to gain insight into the mechanism of transcriptional control and key regulatory events governing human myogenesis in vitro and provide the baseline for further investigation of modifications that occur during muscle pathological processes.

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Cell Harvest and Sample Preparation Prior to MS Analyses

Light (L), medium (M), and heavy (H) labeled cells in DM were harvested after 0, 24, and 72 h, respectively. The cells were washed twice in PBS and lysed by freeze−thaw in 250 mM sucrose, 20 mM Hepes (pH 7.4), 1.5 mM MgCl2, 1 mM sodiumorthovanadate, phosphatase inhibitors (PhosStop, Roche Diagnostics), and protease inhibitors (Complete tablets, Roche Diagnostics).30,31 The whole-cells lysates were cleared by centrifugation, and protein concentrations were determined at this stage spectrophotometrically with the Pierce BCA kit (Thermo Fisher Scientific, Rockford, IL, USA). Equal amounts of protein from differentially labeled cells (light, 0 h; medium, 24 h; heavy, 72 h) were then combined and fractioned by SDS−polyacrylamide gel electrophoresis (SDS-PAGE) using 4−12% acrylamide Bis-Tris precast gels followed by colloidal staining according to the manufacturer’s protocol (NuPAGE Novex Bis-Tris gel; Invitrogen). Whole gels lanes were cut into slices and subjected to in-gel digestion as described previously.32 Briefly, the gel slices were shrunk using acetonitrile, in-gel reduced, and alkylated followed by saturation of the gel pieces with trypsin. Digestion was performed at 37 °C overnight using sequencing grade modified trypsin (Promega), and extracted peptide mixtures were desalted using modified StageTips.33

EXPERIMENTAL PROCEDURES

Human Skeletal Muscle Culture

Human satellite cells were isolated as described previously from a quadriceps muscle biopsy of a 5 day old infant in accordance B


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Journal of Proteome Research LC−ESI−MS/MS Analysis

was excluded from further data analysis. In order to detect significant outlier ratios, an intensity-weighed Significance B pvalue was calculated using Perseus (version 1.3.0.4), which is part of MaxQuant. Protein tables are provided as Tables S2 and S3, Supporting Information.

Mass spectrometric analyses were performed on a LTQ Orbitrap XL (Thermo Fisher Scientific) equipped with a nanoelectrospray ion source (Thermo) coupled to an Agilent 1200 Nanoflow system (Agilent Technologies). The desalted peptide mixtures were injected and separated on an in-house packed fused silica (length 20 cm; i.d. 75 μm) reversed-phase column (3 μm C18, ReproSil-Pur C18 AQ, Dr. Maisch, Germany). Peptides were eluted during a 140 min linear gradient of solvents A (0.5% acetic acid) and B (80% ACN and 0.5% acetic acid) with a flow of 250 nL/min. Upon elution of the peptides into the mass spectrometer, the peptides were ionized using a voltage of 2.3 kV using no sheath and auxiliary gas flow and introduced into the mass spectrometer through an ion transfer tube heated at 275 °C. Spectra were recorded in positive ion mode with data-dependent acquisition automatically switching between recording an MS survey scan of the precursor ions in the Orbitrap and carrying out MS/MS on the 10 most intense ions in the LTQ by collision-induced dissociation. The mass range was set to 300 to 1650 m/z at a resolution of 60 000 at 400 m/z and a target value of 1 × 106 for ions for survey scans in the Orbitrap and 5 × 103 collisioninduced dissociation in the LTQ. Dynamic exclusion was applied to reject ions from repeated MS/MS selection for 90 ms using monoisotopic precursor selection. Singly charged ions or ions with unassigned charge state were also excluded from MS/MS. Data were acquired using Xcalibur software (Thermo Scientific).

Bioinformatic Analysis

Statistical and bioinformatics analyses as well as visualizations were carried out using GProx (version 1.1.13),37 the R framework,38 Cytoscape (version 3.1.1),39 and GraphPad Prism Software (version 5.01; GraphPad Software, Inc., La Jolla,CA, USA). Venn diagrams were generated using the BioVenn web application (http://www.cmbi.ru.nl/cdd/ biovenn/).40 Prism was used to perform two-tailed Student’s t tests to compare data between two groups, and one-way ANOVA, when more than two groups were compared. Significance was determined at p < 0.05. Where appropriate, data are presented as the mean ± SD. Correlations between replicates were also calculated in Prism using Pearson correlation. To address the temporal dynamics of human myoblast differentiation, proteins that were quantified at all time points (in both replicates) were subjected to unsupervised clustering with the fuzzy c-means algorithm in GProX with default parameters. Functional enrichment analyses were subsequently performed for each cluster. First, gene ontology (GO)41 and SMART42 annotations were retrieved from the UniProt database using GProX. Transcription factor targets’ information was retrieved from the Molecular Signatures Database (MSigDB)43 using R. Then, Fisher’s exact test followed by Benjamini and Hochberg p-value adjustment were used to extract terms enriched in each cluster when tested against the remaining clusters. A p-value after adjustment below 0.05 and at least three occurrences in the cluster were required to identify a functional category and/or transcription factor target over-represented in this particular cluster. Enrichment results and protein expression data mapped to pathways in Wikipathways (http://www.wikipathways.org) were visualized using Cytoscape. Finally, disease information was retrieved from the Online Gene Table of Neuromuscular Disorders (GTND) (http://www.musclegenetable.fr/).44 Associations between muscle diseases and proteins in our data set were visualized as a diseasome bipartite map using Cytoscape.

Protein Identification and Quantification

Acquired MS raw data files from two biological replicates were processed with MaxQuant (version 1.3.0.5).34 Enzyme specificity was set to allow for cleavage N-terminal to proline and between aspartic acid and proline (Trypsin/P + DP), and a maximum of two missed cleavages were allowed. Cysteine carbamidomethylation was set as fixed modification, and protein N-terminal acetylation, methionine oxidation, pyroglutamate for N-terminal glutamine, and phophorylation of serine, threonine, and tyrosine (phospho-STY) were selected as variable modifications. A time-dependent mass recalibration algorithm was used to improve the mass accuracy of precursor ions. The derived peak list was searched using the Andromeda search engine integrated in MaxQuant35 against the UniProt human database (2012.11.28) containing 84 945 proteins, to which a list of common contaminants, i.e., the minotaur proteome36 as well as reversed sequences of all entries, had been added. Initial maximal allowed mass tolerance was set to 20 ppm for peptide masses, followed by 6 ppm in the main search and 0.5 Da for fragment ion masses. The minimum peptide length was set to seven amino acid residues, and three labeled amino acid residues were allowed. A 1% false discovery rate (FDR) was required at both the protein and peptide levels. In addition to the FDR threshold, protein identification required at least two peptides and one unique peptide in each replica. For proteins that were identified with a single peptide, detailed information about the MS/MS spectrum, sequence, and precursor m/z is provided in Figure S10 and Table S6, Supporting Information. Both razor and unique peptides, except phospho-STY modified peptides, were considered for protein group quantification. A minimum of two ratio counts was required for confident protein quantification, and the requantify and match between runs functions were enabled. Contaminants’ reverse identification

Western Blot Analysis

Cells were extracted in RIPA buffer (150 mM NaCl, 50 mM Hepes, pH 7.4, 1% NP40, 0.5% sodium deoxycholate, 0.1% SDS, 5 mM EDTA) in the presence of protease inhibitors (Roche) and sonicated. Equal amounts of total protein were separated by SDS-PAGE as described above and then transferred to nitrocellulose membranes. After blocking, the membranes were probed with the indicated antibodies against desmin (DES) (Dako, Glostrup, Denmark), myosin heavychain 3 (MYH3) (Santa Cruz, Dallas, TX, USA), MyoD (MYOD1) (Dako), emerin (EMD) (Novocastra, Ltd., Newcastle Upon Tyne, UK), myogenin (MGN) (Santa Cruz), dysferlin (DYSF) (Novocastra), CD56 (NCAM1) (BD Pharmingen, Franklin Lakes, NJ, USA), KI-67 antigen (MKI67) (Abcam, Cambridge, UK), α-actinin (ACTN2) (Sigma), or PCNA (Santa Cruz). Blots were incubated with the appropriate IgG−HRP-conjugated secondary antibody (GE Healthcare). Immunoreactive bands were visualized using Pierce ECL detection reagent (Thermo). Signals were detected on a film and quantified by densitometry using ImageJ (version 1.48).45 C


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Figure 1. Characterization of the proteome dynamics during myotube formation by quantitative proteomics. (A) Experimental overview of triple encoding SILAC combined with mass spectrometry for analysis of the proteome of differentiating human myoblasts. Three primary muscle cultures were SILAC-labeled with natural and stable isotope substituted arginine (Arg) and lysine (Lys) amino acids. At confluence, proliferating myoblasts were switched to serum-free culture conditions to differentiate into plurinucleated myotubes. Cells were harvested after 0, 24, and 72 h of differentiation and combined after protein normalization. After SDS/PAGE and in-gel digestion, samples were quantitatively analyzed by LC−MS/ MS. We performed two biological replicates of the complete time course experiment. (B) The efficiency and reproducibility of myoblast differentiation in both SILAC experiments (i.e., SILAC 1 and SILAC 2) was evaluated by western blot analysis using antibodies against the proliferation marker MKI67, myosin heavy chain (MYHC-embryonic, MYH3), and myogenic factors MyoD and Myogenin. Emerin, a ubiquitous nuclear envelope protein, was used as a loading control. (C) Density scatter plot assessing the reproducibility of the measured SILAC ratios between the two biological replicas. Log2-transformed normalized protein ratios of the replicates plotted against each other resulted in an almost linear correlation. Pearson correlation coefficient is shown. The color code indicates the percentage of points that are included in a region of a specific color.

Immunocytochemistry

secondary antibodies coupled to Alexa Fluor 488 (Invitrogen) or Cy5 (Jackson Immunoresearch, West Grove, PA, USA). Nuclei were counterstained with DAPI (Sigma). Images were acquired using a Zeiss Observer.Z1 microscope (Zeiss) and analyzed with Metamorph software (Molecular Devices, Sunnyvale, CA, USA).

Briefly, cells were fixed in 4% (w/v) paraformaldehyde (PAF) and then permeabilized with 0.1% Triton X-100. Permeabilized cells were immunostained using primary antibodies against desmin (DES) (Dako), myosin heavy-chain 3 (MYH3) (Santa Cruz), dysferlin (DYSF) (Novocastra), KI-67 antigen (MKI67) (Abcam), or α-actinin (ACTN2) (Sigma) followed by D


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Figure 2. Temporal profiling of the human myoblast proteome during in vitro differentiation. (A) Venn diagram representing the distinct and overlapping proteins regulated after 24 h (M/L ratio) and 72 h (H/L ratio). (B) Comparison of the protein ratios between 24 h (M/L ratio) and 72 h (H/L ratio). Scatter plot of log2-transformed normalized protein ratios. Selected proteins are indicated by their HUGO gene symbol. The black crosses represent regulated protein with a p value < 0.05 at both time points, the blue triangles, regulated proteins with a p value < 0.05 at 24 h (M/L ratio), the red triangles, regulated proteins with a p value 3). See also Figure S7 and Table S4, Supporting Information. The functional network of proteins in (B) is illustrating the set of proteins assigned to the GO_BP terms enriched in cluster 4. Proteins (red circles) are connected to the biological function (white or yellow squares) by a gray line. Protein abbreviations correspond to HUGO gene symbols and are reported in Tables S2 and S3, Supporting Information, with detailed information on the associated proteins.

MKI67. Growth arrest was accompanied by commitment to the muscle differentiation program with increase MYOD1 expression. By 72 h, myoblasts had fused to form multinucleated myotubes that exhibit morphological and biochemical similarities to immature skeletal muscle tissue (Figure 1A) expressing myogenin (MGN) and embryonic myosin heavy chain (MYH3) (Figure 1B). The quantitative proteomics data from the two biological replicates correlated very well, as indicated by an overall Pearson correlation coefficient of 0.82 (Figure 1C). Reliable quantitative measurements were obtained for 2240 proteins across all time points and in both replicates (Table S2, Supporting Information). To evaluate the number of

proteins differentially expressed throughout myotube formation, we calculated the intensity-weighed Significance B p-value. Proteins were considered to be differentially regulated during differentiation if their SILAC ratios showed, within each independent biological replica, p < 0.05 for at least one of the time points (Figures S4 and S5 and Table S3, Supporting Information). Using these criteria, 243 proteins with fold changes ranging between 1.5 and 54.7 were considered to be dynamically regulated (Figure 2). We identified 128 proteins regulated after 24 h (M/L ratio) and 172 regulated after 72 h (H/L ratio). Notably, we observed a strong overlap (57 proteins) between the two time points, representing 45 and F


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tion of protein components of cytoplasmic RNA granules in this cluster (YBX1, PABPC1, DDX3X, CAPRIN1). It has been recently suggested that muscle cell RNP granules are sites of mRNA triage and storage that regulate mRNA stability and translatability via the activities of miRNAs.49 The fusion of postmitotic mononucleated myoblasts to form syncytial myofibers is a critical step in myogenesis and requires coordination among cell migration, adhesion, membrane fusion, and ECM remodeling. We observed several proteins involved in cell−cell adhesion and extracellular matrix organization that exhibited a strong induction after 24 h under differentiation conditions (i.e., members of clusters 2 and 5). A unique pattern of expression was observed for the proteins grouped in cluster 2. Members of this cluster, mainly involved in tissue matrix remodeling, show elevated expression at 24 h and then switch back to their original levels in the differentiated myotubes. Proteins in this cluster include negative regulators of TGF-βdependent signaling (LRP1, CD109, VSN, and CTHRC1) that could be involved in promoting migration of postmitotic myoblasts prior to fusion.50−53 This is further supported by the presence of proteins of similar functionality, mediators of ECM morphogenesis (PLOD1, NUCB1, ANPEP, COL12A1), also identified in cluster 2.54−56 Cluster 5, which contains proteins whose expression is strongly induced and maintained from 24 h onward, was also enriched in extracellular matrix (ECM) components. These include several collagen α isoforms (e.g., COL6A1, COL6A2, COL18A1), HSPG2, EMILIN2, and NID2. The presence of ECM constituents is not surprising since it is well-known that skeletal muscle cells synthesize their own extracellular matrix during the transition from mononucleated myoblast toward syncytial myotubes57,58 and that cell−matrix interactions facilitate myoblast fusion.59 Nevertheless, the identification and quantification of these specific collagens types and ECM components highlight the importance of ECM rearrangement in human primary muscle cells. In addition to ECM rearrangement, myoblast fusion requires the formation of cell−cell contact sites, characterized by a number of molecular changes affecting the sarcolemma, both at the protein and lipid levels, thus facilitating recognition and adhesion.60 Furthermore, cluster 5 contained the fusogenic membrane protein M-Cadherin (CDH15), for which a role in myoblast fusion has been well-established.61 It is also particularly enriched in molecules related to lipid metabolism (CTSA, HEXA, PSAP, CTSA, GBA) and cholesterol homeostasis (AKR1C1, APOE, NPC2) that could influence the changes affecting the membrane lipid bilayer prior to fusion. Finally, the over-representation of lysosomal proteins such as the lysosomal acid hydrolases (CTSA, CTSD) or lysosomal marker LAMP1 in this cluster suggests temporal elevation of the lysosomal degradation pathway during the course of myotube formation. In agreement with this observation, proteolytic systems have been reported to play important roles in remodeling intracellular components during myoblast differentiation.62,63 Cluster 4, the most prominent cluster, contains 78 proteins that showed a gradual increase in expression with myoblast differentiation. This cluster, notable for the high proportion of muscle-specific proteins, was enriched in proteins mainly involved in muscle contraction. It encompassed categories such as sarcomere organization, muscle filament sliding, and muscle organ development. Protein components of the myofibrillar apparatus, myosin light and heavy chains (MYHs and MYLs), actins (ACTs), troponins (TNNs), actinins (ACTNs), titin (TTN), desmin (DES), and

33% of the protein regulated at 24 and 72 h, respectively (Figure 2A). Those proteins presented a high degree of correlation in expression changes (cor. coef: 0.91) and were mostly downregulated (39/57, 68%) (Figure 2B) (e.g., the cell cycle protein CDK1 and the proliferation marker PCNA), suggesting that some changes in the proteome occurred immediately following the initial withdrawal of serum and might be resulting from irreversible cell cycle exit and coordinated onset of the myogenic program. The expression of many housekeeping proteins, such as emerin (EMD) or αtubulin (TUBA1A, TUBA1C, TUBA4A), remained constant throughout differentiation (Figure S6 and Table S3, Supporting Information). Those proteins are commonly used as loading controls in western blot experiments and validate correct normalization of our quantitative proteomic analysis. Dynamic and Functional Characterization of Differentially Regulated Proteins

To better monitor the subtle changes in protein expression during the course of myogenic differentiation, we subjected the 243 proteins differentially regulated to unsupervised clustering using the fuzzy c-means algorithm. The quantitative temporal profiles partitioned into 5 clusters with distinct dynamic expression patterns (Figure 2C and Table S3, Supporting Information). This analysis highlighted two predominant expression patterns: clusters of proteins that were either induced during differentiation (i.e., clusters 4 and 5) or repressed concomitant with cell cycle exit (i.e., clusters 1 and 3). A small cluster of proteins (cluster 2) exhibited unique kinetics, with expression levels rising to a temporary peak 24 h after differentiation induction. To examine whether functionally related proteins and protein classes also demonstrated similar patterns of expression, we tested for enrichment of gene ontology (GO) and SMART terms in each of the 5 clusters (Figures 3A and S7 and Table S4, Supporting Information). Generally, actively proliferating cells require DNA replication, cell cycle control, and mitosis. Cluster 1, with proteins that were downregulated upon initiation of myogenic differentiation, was enriched in such functional categories. This encompassed nuclear proteins involved in cell cycle progression such as the DNA polymerase POLD1, the cyclin-dependent kinase CDK1, and the six canonical members of the minichromosome maintenance (or MCM) protein family (MCM2, MCM3, MCM4, MCM5, MCM6, MCM7). Notably, the two commonly used markers of cell proliferation, MKI67 and PCNA, were also found in clusters 1 and 3, which both included proteins downregulated following differentiation. Additionally, western blotting and immunofluorescence microscopy results were in good agreement with the expression patterns of these two proteins observed by MS (Figures S8 and S9, Supporting Information). Furthermore, cluster 3 indicates that many processes related to mRNA processing and regulation were strongly repressed at the proliferation− differentiation transition point, i.e., 24 h after serum withdrawal. This group of proteins was particularly enriched in poly(A) RNA binding proteins such as RNA helicases belonging to the DEAD-box protein family (EIF4A1, DDX3X, DDX5, DDX21) and cold-shock domain protein family (CSDA, CSDE1, YBX1). These two families are involved in most aspects of RNA metabolism, such as pre-mRNA splicing and translational control.47,48 The notion that tight post-transcriptional regulation of gene expression is required to modulate cell growth and differentiation is further supported by the overrepresentaG


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Figure 4. WikiPathways mapping of striated muscle contraction. Protein expression data are visualized on the striated muscle contraction pathway derived from WikiPathways (http://www.wikipathways.org/index.php/Pathway: WP383). The muscle proteins identified and quantified in our screen are color-coded according to the expression cluster to which they belong, whereas proteins that were not measured in our data set are in light gray. Abbreviations correspond to HUGO gene symbols.

nebulin (NEB), constitute the majority of the muscle contraction proteins in clusters 4 (Figures 3B and 4). As can be seen in Figures 5 and S9, Supporting Information, antibodybased orthologous techniques such as western blotting and immunocytochemistry were in agreement with the dynamics profiles obtained by quantitative proteomics for a subset of proteins belonging to this predominant cluster (MYH3, ACTN2, DES, DYSF).

mononucleated myoblasts to multinucleated myotubes, allowing us to obtain a better overview of the factors involved in myogenic differentiation. Twenty transcriptional regulators, including many well-known regulators of myogenesis, had statistically enriched predicted downstream targets among the regulated proteins (Figure 6A and Table S4, Supporting Information). Exploring the targets of these transcription factors revealed the differential expression of multiple targets of MYOD1, MGN, and MEF2 in cluster 4, i.e., later in the differentiation program (Figure 6B). Predicted targets were mostly muscle-specific proteins induced with myotube formation: components of the myofibrillar apparatus. The myogenic regulatory factor MYOD1 is generally defined as a master switch for skeletal muscle, as its expression alone is sufficient to induce muscle differentiation.64,65 The activation of this transcription factor induces many muscle contractile proteins either directly or through a cascade of additional transcription factors such as MGN and MEF2. Our western blot analysis confirmed that MYOD1 upregulation occurred primarily to induce MGN and that only later in the differentiation program are many of the muscle contractile

Transcriptional Regulation of Differentially Expressed Proteins during Muscle Differentiation in Vitro

In order to determine the underlying relationships between transcription factor activities and clusters of coexpressed target proteins during the course of human myogenic differentiation, we performed a transcription factor target enrichment analysis applied to the significantly regulated proteins within our data set. In other words, we investigated whether the different clusters were enriched for specific transcription factor binding sites in the promoter region of their protein-encoding genes. This in silico analysis revealed distinct waves of transcription regulation that accompanied the phenotypic conversion of H


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Figure 5. Temporal dynamics of selected muscle-specific proteins during in vitro muscle formation. (A) Representative peptide mass spectra from four proteins belonging to cluster 4: myosin heavy chain (MYHC-embryonic, MYH3), α-actinin (ACTN2), desmin (DES), and dysferlin (DYSF). As shown in (B), western blot results for these four molecules closely correlate with the SILAC data (see also Figure S9, Supporting Information). Emerin, a ubiquitous nuclear envelope protein, was used as a loading control. (C) Expression profile and subcellular localization was further investigated by immunohistochemistry of differentiating cultures. Nuclei were counterstained with DAPI (blue). Scale bar, 100 μm.

proteins expressed (Figure 1B). The cluster-specific regulation of targets of various other transcription factors, such as E2Fs family, MYC, or FOXF2, suggests that transient activation of a diverse set of transcription factors is a prerequisite for the different stages of myoblast conversion, i.e., cell cycle exit,

mRNA regulation, ECM remodeling, migration, terminal differentiation, and myofibrillogenesis (Figure 6A and Table S4, Supporting Information). Some of the transcription factors implicated by this in silico analysis as being regulators of myoblast differentiation had no previously appreciated role in in I


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Figure 6. Myogenic transcription factor activity is linked to downstream upregulation of muscle-specific proteins. (A) Enrichment analysis for transcription factor targets among the proteins regulated with myogenesis in vitro. Each cluster from Figure 2C was tested for over-represented predicted transcription factor binding motifs (MSigDB_TF) compared to unregulated proteins using Fisher’s exact test. Transcription factors that were significantly enriched in each of the 5 clusters are summarized in the heat maps (p value < 0.05 after BH correction; occurrence > 3). See also Table S4, Supporting Information. The functional network of proteins in (B) is illustrating the selective enrichment for targets of the myogenic transcription factors MYOD1, MGN, and MEF2 in cluster 4. Transcription factors (yellow triangles) are connected to their predicted downstream targets (red and white circles) by a gray line. Abbreviations correspond to HUGO gene symbols and are reported in Table S3, Supporting Information, with detailed information on the associated proteins.

the formation and maturation of the contractile apparatus in vitro (Figure 4). After 72 h of differentiation, myotubes expressed four different sarcomeric isoforms of myosin heavy chain (MYHs): two developmental isoforms, MYHC-embryonic (MYH3) and MYHC-neonatal (MYH8); MYHC-beta/ slow (MYH7), which is also expressed in cardiac muscle; and MYHC- extraocular/fast (MYH13) (Figures 3B and 4 and Table S3, Supporting Information). These results are in close agreement with previous studies that showed that human satellite cells, when differentiated in vitro, are able to express four types of sarcomeric MYHs: embryonic, neonatal, slow/ cardiac, and fast.23,69 In our experimental setup, no adult fast skeletal muscle isoforms (MYH1, MYH2, MYH4) were detected. Regarding the expression of sarcomeric myosin light chains (MYLs), our analysis demonstrated steady expression of the fast myosin light chains MLC1F/MLC3F (MYL1) across all time points, whereas MLC2F (MYLPF), together with the embryonic form MLC1, embryonic/atrial (MYL4), and MLC1sa (MYL6B), which is primarily expressed in the

vitro muscle formation and will require further investigation (e.g. TFAP4, REPIN1, GTF3A, HIF1). Myofibril Assembly and Muscle Contraction

Myotube formation and maturation are associated with the assembly of the contractile apparatus (or myofibril), which is composed of serial sarcomeres of thick (myosin) filaments alternating with thin (actin) filaments.66 Thin filaments are primarily composed of actin and the regulatory proteins troponin and tropomyosin, whereas thick filaments contain only myosin. Thin and thick filaments also contain accessory proteins such as titin, nebulin, desmin, or α-actinin that stabilize the muscle structure and help to activate contraction. Myofibril formation requires a tightly regulated and ordered expression of various isoforms of sarcomeric proteins and their assembly into the contractile unit.67,68 Using our SILAC quantitative strategy, we followed the expression of a large set of myofibrillar proteins and generated a dynamic map of the developing myofibril in primary human muscle cells, providing valuable insights into J


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Journal of Proteome Research masseter muscle, were induced with myotube formation. The slow skeletal muscle MLC 1s (MYL3) and MLC 2s (MYL2) were not detected; these results were also in accordance with previous findings from our laboratory.23,69 Human satellite cells, when isolated, are capable of reproducing much of the myodifferentiation program in vitro, with the expression of sarcomeric isoforms typical of fetal development and muscle regeneration. Interestingly, we found that over-representation of proteins normally associated with heart development and function (e.g., cardiac muscle contraction and ventricular cardiac muscle tissue morphogenesis) was also associated with myotube formation (Figure 3A and Table S4, Supporting Information). Differentiated cultures accumulated isoforms that are also expressed in cardiac muscle (e.g., myosins MYH7 and MYL4, troponins TNNC1 and TNNI1, as well as specific cardiac isoforms such as α-cardiac actin (ACTC1)) (Figures 3B and 4 and Table S3, Supporting Information). These findings are consistent with the fact that skeletal muscle (especially slow muscle fibers) shares a large number of proteins with the heart, which is also a striated muscle, and that cardiac isoforms are frequently expressed during early skeletal muscle development as well as in regenerating muscle fibers.68 Differentiation of Human Muscle Cells in Vitro: A Snapshot of the Neuromuscular Disorders Landscape

Figure 7. Regulated proteins with known muscle diseases association. Diseasome bipartite map illustrating the association between a set of Kaplan’s GTNMD-based muscle diseases and their causative genes, the protein expression of which is regulated with myotube formation (see also Table S5, Supporting Information). In this network, squares and circles correspond to disorder classes and disease genes, respectively. A protein encoding gene is connected to a disease by a line if it causes it. The size of a square is proportional to the number of genes participating in the corresponding disorder, and proteinencoding genes are color-coded according to the protein expression cluster to which they belong. Abbreviations correspond to HUGO gene symbols and are reported in Table S3, Supporting Information, with detailed information on the associated proteins.

In an attempt to map the muscle diseasome, the collection of all neuromuscular disorders and the genes associated with them, J.C. Kaplan annually publishes a revised list of monogenic muscle diseases: the Gene Table of Neuromuscular Disorders (GTNMD)44 (http://www.musclegenetable.fr). As of December 2013, this database contained 685 disease phenotypes classified into 16 categories and 354 causative genes. In our data set, 99 of the 2240 quantified proteins were genetically linked to a range of muscle diseases, as compiled from Kaplan’s GTNMD (Tables S3−S5, Supporting Information). Among those, 24 were found to be regulated during in vitro differentiation (Figure 7), the majority of which showed gradual upregulation with myotube formation (members of cluster 4) and were associated with causative mutations affecting different elements of the contractile apparatus as well as skeletal and cardiac development. This group of proteins has been implicated previously in a spectrum of pathologies including hereditary cardiomyopathies (nonarrhythmogenic) (e.g., DES, dilated cardiomyopathy), congenital myopathies (e.g., BIN1, myotubular myopathy), metabolic myopathies (e.g., AGL, glycogen storage disease type III), and muscular dystrophies (e.g DYSF, Limb-Girdle muscular dystrophy type 2B), and others (Figure 7 and Table S5, Supporting Information). In addition, mutations in ECM components (e.g., COL6A1 and COL6A2) whose expression was strongly induced and maintained from 24 h onward (members of cluster 5) have been previously implicated in congenital muscular dystrophies. Thus, our SILAC-based quantitative approach not only allowed in vitro muscle formation to be studied but also offered the possibility of following the expression profiles of several disease-associated proteins simultaneously. In addition, this analysis showed that several disease-associated proteins displayed a similar pattern of expression during in vitro muscle formation, highlighting potential similar pathological pathways between disease groups. In conclusion, this study provides a baseline for the comparison of the proteome of human muscle cells under both diseased and healthy conditions and could

provide valuable insights into the pathological mechanisms underlying degenerative muscle disorders.

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CONCLUSIONS Human postnatal myogenesis and skeletal muscle regeneration involve the differentiation of satellite cells, muscle stem cells, through coordinated muscle-specific gene expression, cell cycle exit, migration, and fusion into syncytial muscle fibers. In order to obtain a better understanding of the cell signaling orchestra governing the transition from mononucleated cells to postmitotic plurinucleated myotubes, we successfully applied a SILAC-based quantitative proteomics approach to explore and characterize the proteome of primary human myoblasts during in vitro differentiation. To our knowledge, this study represents the first MS-based proteomics analysis investigating human myogenesis in vitro from human primary culture. Using a triple SILAC encoding strategy, we generated dynamic expression profiles during the course of myogenic differentiation and demonstrated that changes in the expression of regulated proteins occurred in multiple, sequential steps that form distinct waves consistent with the mitotic to postmitotic cellular transition and the dramatic change in cellular phenotype accompanying myogenic differentiation. Exit from the cell cycle occurred immediately after serum withdrawal and was represented by repression of cell cycle regulatory proteins as well as many processes related to splicing and RNA metabolism (clusters 1 and 3). A second wave was represented K



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ACKNOWLEDGMENTS We gratefully thank J. Bunkenborg, A.M.M. Nordborg, L.M. Harder, and D. Pultz (University of Southern Denmark) for support, advice, and assistance. This work was supported by The Danish Council for Independent Research−Medical Sciences (F.S.S.) and the Novo Nordisk Foundation. M.C.L.B. is supported by the AFM (Association Française contre les Myopathies). I.K. is supported by grants from the Danish Council for Independent Research, Natural Sciences (F.N.U.) and Medical Sciences (F.S.S.).

by a sharp increase in levels of proteins involved in cell−cell adhesion and ECM organization (clusters 2 and 5). Finally, by 72 h, many cytoskeletal proteins, elements of the contractile apparatus, were dramatically upregulated, coinciding with the fusion and maturation into multinucleated myotubes (cluster 4). The expected expression patterns of many known musclespecific proteins demonstrated the validity of this proteomics approach to studying myogenesis. In summary, the data presented here offer important insights into the proteome dynamics underlying human myoblast differentiation in vitro and highlight important reprogramming of several key cellular functions. Those changes in the proteome could be attributed to differential transcriptional regulation during in vitro differentiation. We believe that our data constitute a rich resource that complements and enhances our mechanistic understanding of human postnatal myogenesis and regeneration as well as myofibrillogenesis. This resource could also serve as a reference/baseline for future characterization of fundamental alterations affecting the muscle proteome under pathological conditions.

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ABBREVIATIONS dFBS, dialyzed FBS; DM, differentiation medium; ECM, extracellular matrix; GM, growth medium; GO, gene ontology; GTNMD, Gene Table of Neuromuscular Disorders; LTQ, linear trap quadrupole; MPD, mean population doublings; MSigDB, Molecular Signatures Database; SILAC, stable isotope labeling by amino acids in cell culture; SMART, simple modular architecture research tool

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ASSOCIATED CONTENT

S Supporting Information *

REFERENCES

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Supplementary text. Figure S1: Effect of dialyzed FBS (dFBS) during cell expansion on growth, myogenicity, and differentiation of human myoblasts. Figure S2: Effect of SILAC DMEM formulation on growth, myogenicity, and differentiation of human myoblasts. Figure S3: SILAC labeling efficiency in human primary myoblasts. Figure S4: Correlation between SILAC ratios obtained from two independent studies of human myoblast differentiation. Figure S5: SILAC protein ratios distribution during human myoblast differentiation in vitro. Figure S6: Temporal expression profile of the nuclear protein Emerin during in vitro muscle formation applying SILAC-based quantitative proteomics. Figure S7: Enrichment analysis for GO Cellular Compartment (GO_CC), GO Molecular Function (GO_MF) as well as domain family (SMART) terms over-represented in each regulated cluster. Figure S8: Protein expression profiles of two proliferation markers: MKI67 and PCNA. Figure S9: Western blot analysis of selected regulated candidates during in vitro muscle formation. Figure S10: MS/MS spectra for the single peptide based identification. Table S1: Evaluation of SILAC labeling efficiency of human primary myoblasts. Table S2: Identified and quantified proteins from differentiating human muscle cells. Table S3: Proteins differentially expressed with in vitro differentiation. Table S4: Functional annotation enrichment for proteins with similar regulation pattern during myotube formation in vitro. Table S5: Proteins with known muscle diseases association. Table S6: Single peptide identification details. The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/ acs.jproteome.5b00397.

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AUTHOR INFORMATION

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*E-mail: [email protected]. Phone: +45 6550 2494. Fax: +45 6593 3018. Notes

The authors declare no competing financial interest. L


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