Sporadic inclusion body myositis-derived myotube culture revealed muscle cell-autonomous expression profiles

Naoki Suzuki; Makoto Kanzaki; Masashi Koide; Rumiko Izumi; Ryo Fujita; Tadahisa Takahashi; Kazumi Ogawa; Yutaka Yabe; Masahiro Tsuchiya; Masako Suzuki; Ryuhei Harada; Akiyuki Ohno; Hiroya Ono; Naoko Nakamura; Kensuke Ikeda; Hitoshi Warita; Shion Osana; Yoshitsugu Oikawa; Takafumi Toyohara; Takaaki Abe; Muliang Rui; Satoru Ebihara; Ryoichi Nagatomi; Yoshihiro Hagiwara; Masashi Aoki

doi:10.1371/journal.pone.0306021

. 2024 Aug 1;19(8):e0306021. doi: 10.1371/journal.pone.0306021

Sporadic inclusion body myositis-derived myotube culture revealed muscle cell-autonomous expression profiles

Naoki Suzuki ^1,^2,^*, Makoto Kanzaki ³, Masashi Koide ⁴, Rumiko Izumi ¹, Ryo Fujita ⁴, Tadahisa Takahashi ⁴, Kazumi Ogawa ^1,⁴, Yutaka Yabe ⁴, Masahiro Tsuchiya ⁵, Masako Suzuki ¹, Ryuhei Harada ¹, Akiyuki Ohno ¹, Hiroya Ono ^1,⁶, Naoko Nakamura ¹, Kensuke Ikeda ¹, Hitoshi Warita ¹, Shion Osana ⁷, Yoshitsugu Oikawa ^8,⁹, Takafumi Toyohara ^9,¹⁰, Takaaki Abe ^9,^10,¹¹, Muliang Rui ², Satoru Ebihara ², Ryoichi Nagatomi ⁷, Yoshihiro Hagiwara ⁴, Masashi Aoki ^1,^*

Editor: Keisuke Hitachi¹²

¹Department of Neurology, Tohoku University Graduate School of Medicine, Sendai, Japan

²Department of Rehabilitation Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan

³Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan

⁴Department of Orthopedic Surgery, Graduate School of Medicine, Tohoku University, Sendai, Japan

⁵Department of Nursing, Tohoku Fukushi University, Sendai, Japan

⁶Department of Neurology, National Hospital Organization Iwate Hospital, Ichinoseki, Iwate, Japan

⁷Division of Biomedical Engineering for Health and Welfare, Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan

⁸Department of Pediatrics, Tohoku University Graduate School of Medicine, Sendai, Japan

⁹Division of Nephrology, Endocrinology and Vascular Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan

¹⁰Department of Medical Science, Tohoku University Graduate School of Biomedical Engineering, Sendai, Japan

¹¹Department of Clinical Biology and Hormonal Regulation, Tohoku University Graduate School of Medicine, Sendai, Japan

¹²Fujita Health University, JAPAN

Competing Interests: The authors have declared that no competing interests exist.

^✉

* E-mail: aokim@med.tohoku.ac.jp (MA); naoki.suzuki.e3@tohoku.ac.jp (NS)

Roles

Naoki Suzuki: Conceptualization, Data curation, Formal analysis, Investigation, Resources, Writing – original draft, Writing – review & editing

Makoto Kanzaki: Investigation, Resources

Masashi Koide: Investigation, Resources

Rumiko Izumi: Data curation, Investigation, Resources, Visualization

Ryo Fujita: Investigation, Resources

Tadahisa Takahashi: Investigation, Resources

Kazumi Ogawa: Investigation, Resources

Yutaka Yabe: Investigation

Masahiro Tsuchiya: Investigation

Masako Suzuki: Data curation, Formal analysis, Investigation, Resources

Ryuhei Harada: Investigation, Writing – review & editing

Akiyuki Ohno: Data curation, Investigation

Hiroya Ono: Data curation, Investigation

Naoko Nakamura: Investigation

Kensuke Ikeda: Data curation, Investigation

Hitoshi Warita: Investigation

Shion Osana: Investigation

Yoshitsugu Oikawa: Investigation

Takafumi Toyohara: Investigation

Takaaki Abe: Funding acquisition, Investigation

Muliang Rui: Investigation, Validation

Satoru Ebihara: Validation

Ryoichi Nagatomi: Funding acquisition, Investigation

Yoshihiro Hagiwara: Investigation, Resources

Masashi Aoki: Conceptualization, Funding acquisition, Investigation, Writing – review & editing

Keisuke Hitachi: Editor

PMCID: PMC11293708 PMID: 39088432

Abstract

Sporadic inclusion body myositis (sIBM) is a muscle disease in older people and is characterized by inflammatory cell invasion into intact muscle fibers and rimmed vacuoles. The pathomechanism of sIBM is not fully elucidated yet, and controversy exists as to whether sIBM is a primary autoimmune disease or a degenerative muscle disease with secondary inflammation. Previously, we established a method of collecting CD56-positive myoblasts from human skeletal muscle biopsy samples. We hypothesized that the myoblasts derived from these patients are useful to see the cell-autonomous pathomechanism of sIBM. With these resources, myoblasts were differentiated into myotubes, and the expression profiles of cell-autonomous pathology of sIBM were analyzed. Myoblasts from three sIBM cases and six controls were differentiated into myotubes. In the RNA-sequencing analysis of these “myotube” samples, 104 differentially expressed genes (DEGs) were found to be significantly upregulated by more than twofold in sIBM, and 13 DEGs were downregulated by less than twofold. For muscle biopsy samples, a comparative analysis was conducted to determine the extent to which “biopsy” and “myotube” samples differed. Fifty-three DEGs were extracted of which 32 (60%) had opposite directions of expression change (e.g., increased in biopsy vs decreased in myotube). Apolipoprotein E (apoE) and transmembrane protein 8C (TMEM8C or MYMK) were commonly upregulated in muscle biopsies and myotubes from sIBM. ApoE and myogenin protein levels were upregulated in sIBM. Given that enrichment analysis also captured changes in muscle contraction and development, the triggering of muscle atrophy signaling and abnormal muscle differentiation via MYMK or myogenin may be involved in the pathogenesis of sIBM. The presence of DEGs in sIBM suggests that the myotubes formed from sIBM-derived myoblasts revealed the existence of muscle cell-autonomous degeneration in sIBM. The catalog of DEGs will be an important resource for future studies on the pathogenesis of sIBM focusing on primary muscle degeneration.

Introduction

Sporadic inclusion body myositis (sIBM) is a defined muscle disease prevalent in older individuals [1–3], characterized by specific patterns of muscle involvement, including finger flexors, knee extensors, and dysphagia [4]. Pathologically, sIBM is identified by the presence of rimmed vacuoles and inflammatory cell invasion in non-necrotic muscle fibers [5]. Despite these distinctive features, the underlying pathomechanism of sIBM remains incompletely understood.

Controversy surrounds whether sIBM is a primary autoimmune disease or a degenerative muscle disorder with secondary inflammation. Reports suggest the involvement of the interferon-gamma mediated signaling pathway [6], myeloid dendritic and plasma cells [7], and highly differentiated cytotoxic T cells [8] in sIBM pathology. Additionally, anti-cytosolic 5’-nucleotidase 1A autoantibodies are found in the serum of patients with sIBM [9]. However, the disease often proves resistant to immunosuppressive therapy, emphasizing the importance of muscle degeneration in sIBM etiology [10].

Muscle biopsy is necessary for the diagnosis of sIBM [11, 12]. The rest of the diagnostic samples can be used for research, such as in gene expression profiling; for example, gene sets to differentiate sIBM biopsy samples from other myositis using support vector machine-learning system are revealed [13]. Other groups analyzed two microarray datasets [8, 14] derived from the Gene Expression Omnibus database and picked-up genes as a hub of a pathological network [15]. As the pathology of sIBM shows the involvement of cells such as inflammatory cell infiltration, fibrosis, and adipose tissues [16, 17], challenges arise due to the potential confounding effects of non-muscle cells in expression data analysis.

A significant development in understanding sIBM occurred in 1994 when ApoE immunoreactive deposits were first identified in rimmed vacuoles of sIBM muscle biopsy samples [18]. Subsequent findings implicated aberrant cholesterol metabolism in sIBM muscles [19, 20]. An sIBM mouse model overexpressing amyloid beta was utilized [21], yet the mechanisms of abnormal protein accumulation in muscle degeneration remain unclear.

Previously, we established a method of collecting CD56-positive myoblasts from human skeletal muscles derived from muscle biopsy samples [22, 23]. We hypothesized that the myoblasts could serve as a valuable resource to investigate the cell-autonomous pathomechanism of sIBM. The myoblasts were differentiated into myotubes, and the expression profiles were analyzed to gain insights into the cell-autonomous pathology of sIBM.

Materials and methods

Study population

The study protocol was approved by the Tohoku University Hospital’s Institutional Review Board (Approval nos. 2014-1-703, 2016-1-884, 2019-1-493, 2022-1-848), and written informed consent was obtained from all participants. Data was collected on 12/10/2020.

Sample collection from patients with sIBM

From 26/01/2015 to 31/05/2018, we performed muscle biopsies on 13 patients who were presumptively diagnosed with sIBM. Muscle samples were collected from nine patients who agreed to undergo a biopsy. The number of patients evaluated was restricted because of the limited access to the fluorescence-activated cell sorting (FACS) system at our institute and the requirement for performing the procedure on the same day as the muscle biopsy.

The cells prepared from each muscle by FACS were separated into three replicates for characterization and culture. In each patient, muscle biopsy specimens (approximately 300 mg) were obtained from the muscle belly of the biceps brachii or lower proximal muscles (Table 1). Three lines of actively proliferating myoblasts were used for the analysis.

Table 1. Characteristics of patients with sporadic inclusion body myositis.

Case No.	Age at biopsy	Sex	Diagnosis	muscle ID	Site of biopsy	Myoblast ID	Biopsy RNA-seq
1	86	F	sIBM	C1017	BB	sIBM Myoblast 2
2	69	M	sIBM	C1047	RF	sIBM Myoblast 6	sIBM Biopsy 1
3	69	M	sIBM	C1054	BB	sIBM Myoblast 7	sIBM Biopsy 2
4	73	M	sIBM	C1092	VL		sIBM Biopsy 3
5	62	M	sIBM	C1220	BB	sIBM Myoblast 8
6	77	M	neurogenic atrophy	C1053	BB		Disease control Biopsy 1
7	65	F	neurogenic atrophy	C922	Gc		Disease control Biopsy 2
8	71	F	DMD carrier	C1032	BB		Disease control Biopsy 3
9	76	M	amyloidosis	C1049	RF		Disease control Biopsy 4
10	56	F	Rotator cuff tears		subscapularis	SSC13
11	60	F	Rotator cuff tears		subscapularis	SSC14
12	69	F	Rotator cuff tears		subscapularis	SSC16
13	60	M	Rotator cuff tears		subscapularis	SSC18
14	69	M	Rotator cuff tears		subscapularis	SSC4
15	69	M	Rotator cuff tears		subscapularis	SSC8

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BB; biceps brachii, DMD; Duchenne muscular dystrophy, Gc; Gastrocnemius, RF; rectus femoris, VL; vastus lateralis

Sample collection from the control participants (patients with rotator cuff tears [RCT]).

From 26/01/2015 to 28/12/2015, arthroscopic RCT repairs were performed in 42 patients who were unresponsive to conservative treatments [23]. Muscle samples were collected from 19 patients who agreed to undergo a biopsy. None of the patients had tears in the intact subscapularis (SSC) tendon based on both magnetic resonance imaging and arthroscopic findings. No patients had muscular disease, neurovascular disorders, paralysis, or trauma. Muscle biopsy specimens (approximately 300 mg) were obtained from the same portion of the muscle belly of the SSC in each patient who underwent arthroscopic surgery (Table 1) [23].

Primary myoblast isolation

Human satellite cells were isolated from the muscles of patients who agreed to undergo biopsy. All experiments were performed in accordance with relevant guidelines and regulations as described elsewhere [23, 24]. Briefly, the tissue was minced and digested with 0.2% collagenase (Wako Pure Chemicals Industries) and 0.1% DNase I (Sigma-Aldrich, St. Louis, MO, USA), filtered through a 70-μm cell strainer (BD Biosciences, Franklin Lakes, NJ, USA), and centrifuged at 700 × g for 20 min. Pellets were resuspended in phosphate-buffered saline (PBS) containing 1% bovine serum albumin (BSA; Sigma-Aldrich) and then incubated with an Fc receptor blocking solution (Human TruStain FcX, 1:20 in the staining buffer; BioLegend, San Diego, CA, USA). Then, the samples were labeled with the following monoclonal antibodies (all from BioLegend and all at 1:20 dilution): fluorescein isothiocyanate (FITC)-conjugated anti-CD45 (clone HI30), FITC-conjugated anti-CD11b (clone ICRF444), FITC-conjugated anti-CD31 (clone WM59), phycoerythrin (PE)/Cy7-conjugated anti-CD34 (clone 581), allophycocyanin (APC)-conjugated anti-CD56 (clone MEM-188), and PE-conjugated anti-PDGFRα (clone 16A1). The negative set included blood markers CD11b and CD45 and endothelial markers CD31 and CD34. Although CD34 is expressed by the majority of mouse satellite cells [25], human muscle-derived CD34⁺ cells are myogenic and adipogenic, whereas CD34⁻ cells are myogenic but not adipogenic [26]. Therefore, CD34 was used as a negative selection marker. Human satellite cells were defined as single live mononuclear CD11b⁻CD31⁻CD34⁻CD45⁻CD56⁺ cells. FACS was performed on a FACS ARIA II flow cytometer (BD Biosciences). Cells were seeded onto 24-well chamber slides coated with Matrigel (Dow Corning, Corning, NY, USA) in a growth medium containing DMEM/Ham’s F10 mixture supplemented with 20% fetal bovine serum, 1% penicillin—streptomycin, 1% chicken embryonic extract (United States Biological, Salem, MA, USA), and 2.5 ng/mL basic fibroblast growth factor (Thermo Fisher Scientific, Waltham, MA, USA) and cultured at 37°C in a 5% CO₂ atmosphere. When cells reached 60%–80% confluence, adherent cells were dissociated and split onto a new Matrigel-coated 15-cm dish to expand the activated satellite cells. Activated satellite cells (myoblasts) were suspended in Cell Banker (Takara, CB011, Japan) and stored in liquid nitrogen.

Cell culture

Human myoblasts were cultured using media purchased from Lonza (Walkersville, MD, USA). Three days after plating, the cells reached 80%–90% confluence (day 0). Then, differentiation was induced by switching the growth medium to DMEM supplemented with 2% horse serum, 30 μg/mL penicillin, and 100 μg/mL streptomycin (differentiation medium). The differentiation medium was changed every 24 h during the 7–8 days of differentiation.

RNA extraction and sequencing analysis

Cultured myotubes were collected to extract the total RNA, which was performed using an RNeasy micro kit (Qiagen, Germany) according to the manufacturer’s protocol. RNA-sequencing (RNA-seq) libraries were prepared using a TruSeq RNA-stranded mRNA Sample Prep Kit (Illumina, CA, USA). These libraries were clonally amplified on a flow cell and sequenced on a HiSeq2500 (HiSeq Control Software v2.2.58, Illumina) with a 51-mer single-end sequence. Image analysis and base calling were performed using Real-Time Analysis Software (v1.18.64, Illumina). For data analysis, UCSC hg19 and RefSeq were used as the reference human genome and gene model, respectively. For gene expression analysis, single-end reads were mapped to the human genome using TopHat (ver. 2.1.0) [27]. Cufflinks (ver. 2.2.1) was used to estimate the gene expression levels based on fragments per kilobase of the exon model per million mapped fragments [28]. Gene expression levels were compared between control cells and sIBM cells using Cuffdiff (ver. 2.2.1). The False Discovery Rate (FDR) cutoff value was set at 0.05. Unmapped reads are 4–7% % (S1 Table).

Immunohistochemistry and immunocytochemistry

The biopsy sections and cultured myotubes were washed with PBS and fixed for 20 min with 2% paraformaldehyde in PBS containing 0.1% Triton X-100. Samples were washed and blocked in PBS containing 5% CS and 1% BSA at room temperature. For immunofluorescence analysis, anti-desmin antibody (MAB-606102, Diagnostic BioSystems: DBS), ApoE (16H22L18, Invitrogen), dystrophin (NCL-Dys1, Leica), caveolin-3 (sc-55518, Santa Cruz), MYMK (PA5-63180, Invitrogen), amyloid oligomers (A11; SPC-506D, StressMarQ), were used as the first antibody, and Alexa Fluor 488 or 568-conjugated anti-IgG was used as the secondary antibody, in a solution of 1% BSA in PBS. The samples were mounted on glass slides with Vectashield (Vector Laboratories, Burlingame, CA, USA) and observed with a confocal fluorescence microscope (Fluoview FV-1000; Olympus, Tokyo, Japan) or fluorescence microscope (BZ-X700; Keyence).

Immunoblotting

For immunoblot analysis, skeletal muscle protein was extracted from the human myotubes, as described previously [29]. Total cell proteins were extracted from cells with radio-immunoprecipitation (RIPA) buffer (ATTO) and measured using a Bicinchoninic Acid Kit (Thermo Fisher Scientific). After the adjustment of the protein concentration, protein samples were reacted with Laemmli buffer at 95°C for 5 min and separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis using 10%–20% polyacrylamide gels (ATTO) under constant voltage of 200 V for 60 min. Then, the separated proteins were transferred to polyvinylidene difluoride membranes (Millipore, MA, USA). After blocking with 2% BSA (Pierce), membranes were probed with the indicated primary antibodies including ApoE (16H22L18, Invitrogen), myogenin (sc-12732, Santa Cruz), and GAPDH (2118L, CST) overnight at 4°C. Immunolabeling was visualized by incubation with horseradish peroxidase-linked secondary antibodies (5,000-fold dilution) at room temperature for 1 h, followed by treatment with an enhanced chemiluminescence prime reagent (GE Healthcare, IL, USA); images were captured using an LAS-3000 Image Reader (Fujifilm, Tokyo, Japan). Blots were labeled with anti-GAPDH antibodies as the gel loading control.

Statistical analysis

Statistical analyses were performed using Student’s t-test, analysis of variance with Tukey’s multiple comparison test, or Wilcoxon signed-rank test, and p-values < 0.05 indicated a statistically significant difference unless otherwise specified. Data are expressed as means ± SE unless otherwise specified.

Results

Myoblasts from three sIBM subjects and six controls were subjected to differentiation, resulting in the formation of myotubes (referred to as “myotube”: Table 1 and Fig 1A).

Fig 1 — A. Schema of collecting myoblast from the muscle biopsy sample. The tissue was minced and digested with 0.2% collagenase and 0.1% DNase I. CD11b⁻CD31⁻ CD34⁻ CD45⁻ CD56⁺ cells were sorted using FACS. Purified myoblasts were expanded in the growth medium. Myoblasts were differentiated into myotubes in the differentiation medium. B–G. Myotubes derived from patients with sIBM (B, C) and control (D, E). Desmin (B, D) and Dapi (C, E) staining. Overlay images are also shown (D, G). Scale bar, 50 μm. H. 95–98% of the nuclei exhibited colocalization with Desmin. sIBM, sporadic inclusion body myositis.

Immunocytochemistry analysis demonstrated the presence of desmin-positive multinucleated myotubes following the differentiation process in both the sIBM and control groups (Fig 1B–1G). When quantified, it was determined that 95–98% of the nuclei exhibited colocalization with Desmin, as depicted in Fig 1H. Subsequently, RNA was extracted from these myotubes (Fig 1A), and RNA-seq was conducted (Fig 2). In both control and sIBM-derived myotubes, the expression of human muscle stem cell markers such as Integrin alpha 7 (ITGA7), m-cadherin (CDH15), and CD82 was observed to be high (S1 Fig). The results revealed a total of 104 genes that exhibited a significant upregulation of more than two-fold in sIBM (Table 2).

Fig 2 — A. Heat maps of three sIBM and six control myotube samples. B. The enrichment of the genes differentially expressed in the sIBM and control groups was analyzed by GO_BP term analysis using the Subio platform. The top terms are listed with >4 overlapped genes, with p-values < 0.05 (Fisher’s exact test). C. The enrichment of the genes differentially expressed in the sIBM and control groups were analyzed by GO_MF term analysis using the Subio platform. The top terms are listed with >4 overlapped genes, with p-values < 0.05 (Fisher’s exact test). D. Venn diagram showing overlapped dysregulated genes between sIBM myotubes (991 genes) and sIBM biopsy (901 genes). Differentially expressed genes (DEGs: fold-change difference of |1.5|) were compared. Fifty-three genes are commonly dysregulated. E. Volcano plot of the genes differentially expressed in sIBM and SSC focusing genes are plotted on the figures. sIBM, sporadic inclusion body myositis.

Table 2. Upregulated genes in sIBM myotube (vs control, >×2, p < 0.05, Student’s t-test (equal variance)).

Cell-autonomous expression analysis from sIBM myotube. A total of 104 genes are listed. sIBM, sporadic inclusion body myositis.

Gene	Gene Name	Fold Change	P-Value
MYL1	myosin light chain 1	11.202059	0.007286711
MYL2	myosin	9.947378	1.29E-04
TNNT3	troponin T3, fast skeletal type	9.788654	0.002023014
ACTA1	actin, alpha 1, skeletal muscle	8.129974	4.51E-04
MYBPH	myosin binding protein H	7.952435	7.49E-04
TNNC2	troponin C2, fast skeletal type	6.319282	7.47E-04
F13A1	coagulation factor XIII A chain	6.295651	0.03281219
MYLPF	myosin light chain, phosphorylatable, fast skeletal muscle	6.110357	0.003378833
COX6A2	cytochrome c oxidase subunit 6A2	5.6563983	0.017002339
TNNT1	troponin T1, slow skeletal type	5.2325187	0.003490027
MYH3	myosin heavy chain 3	5.1348267	0.026199384
TNNC1	troponin C1, slow skeletal and cardiac type	5.116753	0.00108173
MYL6B	myosin light chain 6B	5.106448	2.46E-04
HSPB8	heat shock protein family B (small) member 8	4.745588	6.45E-04
TNNI1	troponin I1, slow skeletal type	4.6149263	0.007806895
MYL4	myosin light chain 4	4.465095	0.009941747
DES	desmin	4.4114947	0.010139073
BIN1	bridging integrator 1	4.243511	0.001979603
ENO3	enolase 3	4.2209435	0.001152897
TMEM8C	transmembrane protein 8C	4.1701674	0.005040719
KLHL41	kelch like family member 41	3.6543784	0.026659327
SLN	sarcolipin	3.5593212	0.012243188
STAC3	SH3 and cysteine rich domain 3	3.5460794	0.015242067
ANKRD1	ankyrin repeat domain 1	3.441077	0.038272817
ACTN2	actinin alpha 2	3.3681853	3.75E-04
MIR133B	microRNA 133b	3.3491333	0.013239365
MYOG	myogenin	3.3376992	0.022312023
CASQ2	calsequestrin 2	3.2697413	0.004478621
TPM3	tropomyosin 3	3.1789114	7.78E-04
IL32	interleukin 32	3.1274703	0.030406158
MYH7	myosin heavy chain 7	3.0794365	9.46E-04
MEF2C	myocyte enhancer factor 2C	3.047847	0.010303746
FABP3	fatty acid binding protein 3	2.9947274	0.008757984
ACTC1	actin, alpha, cardiac muscle 1	2.895736	0.043732658
HSPB3	heat shock protein family B (small) member 3	2.8300886	0.002575204
RASSF4	Ras association domain family member 4	2.8004258	0.016659606
MURC	-	2.7417965	0.001631513
HN1	-	2.6370249	0.009545088
CDKN1A	cyclin dependent kinase inhibitor 1A	2.485724	0.002141749
DMPK	dystrophia myotonica protein kinase	2.4113045	0.02649946
MLLT11	myeloid/lymphoid or mixed-lineage leukemia; translocated to, 11	2.3682325	0.00156106
CFL2	cofilin 2	2.3300521	2.23E-04
UCP2	uncoupling protein 2	2.2923715	6.50E-05
CKM	creatine kinase, M-type	2.2887108	0.018692916
DCLK1	doublecortin like kinase 1	2.27428	0.014638593
APOE	apolipoprotein E	2.258964	0.02849325
STMN1	stathmin 1	2.2580466	0.002031321
SNORD24	-	2.2476733	0.002950982
SETD7	SET domain containing lysine methyltransferase 7	2.2390144	0.00811696
ZNF106	zinc finger protein 106	2.1539176	0.005711007
PRDX6	peroxiredoxin 6	2.078649	0.006655635
MRAS	muscle RAS oncogene homolog	2.0655692	0.035309568
MIR4787	microRNA 4787	2.021805	0.006221586
CYB5R1	cytochrome b5 reductase 1	1.9932206	0.014857224
NEXN	nexilin F-actin binding protein	1.9889293	0.028174449
BLCAP	bladder cancer associated protein	1.9670132	0.009212402
MYH8	myosin heavy chain 8	1.965625	0.001588375
MAPRE3	microtubule associated protein RP/EB family member 3	1.9434834	2.23E-04
TUBA1A	tubulin alpha 1a	1.9425162	0.011722326
KIF5B	kinesin family member 5B	1.9053978	0.03412914
ATP2A2	ATPase sarcoplasmic/endoplasmic reticulum Ca2+ transporting 2	1.9013083	0.003384043
MIR27A	-	1.8992655	0.007567231
CTSH	cathepsin H	1.8868161	0.030131867
SMPX	small muscle protein, X-linked	1.876876	0.001038277
TPM2	tropomyosin 2 (beta)	1.8715552	0.043131925
FKBP3	FK506 binding protein 3	1.8516325	9.88E-04
KLHDC2	kelch domain containing 2	1.8059789	0.011938629
HNRNPDL	heterogeneous nuclear ribonucleoprotein D like	1.7927606	7.21E-05
RTN2	reticulon 2	1.7837111	0.008038428
UQCR10	ubiquinol-cytochrome c reductase, complex III subunit X	1.7718846	0.001749373
IDH2	isocitrate dehydrogenase (NADP(+)) 2, mitochondrial	1.7091504	0.014825196
ODC1	ornithine decarboxylase 1	1.7080046	0.026313692
HSPB2	heat shock protein family B (small) member 2	1.7018151	0.012277631
RAPSN	receptor associated protein of the synapse	1.6918406	0.01916177
ITGA6	integrin subunit alpha 6	1.6912874	0.026712555
MIR3960	-	1.6898465	4.16E-04
SYNPO2	synaptopodin 2	1.6888578	5.24E-05
SBDS	SBDS, ribosome assembly guanine nucleotide exchange factor	1.6792147	0.007196609
PRUNE2	prune homolog 2	1.6792002	0.04550971
TRIM72	tripartite motif containing 72	1.6562946	7.82E-04
WSB2	WD repeat and SOCS box containing 2	1.6523238	0.009012659
CHCHD10	coiled-coil-helix-coiled-coil-helix domain containing 10	1.6480478	0.004553978
AK1	adenylate kinase 1	1.6430076	0.022719005
NDUFS5	NADH:ubiquinone oxidoreductase subunit S5	1.6388379	0.004627282
CALM1	calmodulin 1	1.6350479	0.03881275
GYS1	glycogen synthase 1	1.6332341	2.07E-04
SYTL2	synaptotagmin like 2	1.628396	3.04E-04
TIMM8B	translocase of inner mitochondrial membrane 8 homolog B	1.6226355	0.002241131
HACD1	3-hydroxyacyl-CoA dehydratase 1	1.6016754	8.34E-05
CACNB1	calcium voltage-gated channel auxiliary subunit beta 1	1.5958093	0.01881004
FNDC5	fibronectin type III domain containing 5	1.5868237	0.037550054
RAPGEF1	Rap guanine nucleotide exchange factor 1	1.5625403	0.002484248
CCT2	chaperonin containing TCP1 subunit 2	1.554814	0.004175162
SYNC	syncoilin, intermediate filament protein	1.5515491	3.46E-04
COX6C	cytochrome c oxidase subunit 6C	1.5454249	0.00239981
HRC	histidine rich calcium binding protein	1.5410172	4.67E-04
COX11	COX11, cytochrome c oxidase copper chaperone	1.5325474	1.85E-05
GRASP	general receptor for phosphoinositides 1 associated scaffold protein	1.5297244	0.040888462
NDUFS2	NADH:ubiquinone oxidoreductase core subunit S2	1.5288111	5.10E-05
UQCRC2	ubiquinol-cytochrome c reductase core protein II	1.5287356	0.003558046
SRPK3	SRSF protein kinase 3	1.5262501	0.01884095
UQCRQ	ubiquinol-cytochrome c reductase complex III subunit VII	1.5190833	0.018657938
MAP1A	microtubule associated protein 1A	1.5157436	0.017696884
GLO1	glyoxalase I	1.5097214	0.002272782

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Among these upregulated genes, myoblast differentiation factor, myogenin was upregulated in sIBM, as reported previously [30]. Conversely, thirteen differentially expressed genes (DEGs) were downregulated by less than twofold (Table 3).

Table 3. Downregulated genes in sIBM myotube (vs SSC, >×2, p < 0.05, Student’s t-test (equal variance)).

Cell-autonomous expression analysis from sIBM myotube. Thirteen genes are listed. sIBM, sporadic inclusion body myositis.

Gene	Gene Name	Fold Change	P-Value
SERPINE2	serpin family E member 2	0.22732568	0.014635123
GAS6	growth arrest specific 6	0.27426982	0.014784024
SNORD50B	-	0.3030194	0.013391182
SNORD30	-	0.30977944	0.013535343
IGFBP7	insulin like growth factor binding protein 7	0.3813738	0.001449735
MT2A	metallothionein 2A	0.3937795	0.022868155
IGFBP4	insulin like growth factor binding protein 4	0.41521716	0.049309194
MIR1282	microRNA 1282	0.42054167	0.025922615
IGFBP5	insulin like growth factor binding protein 5	0.42213562	0.010698475
ITGBL1	integrin subunit beta like 1	0.44444004	0.006151323
ITGB5	integrin subunit beta 5	0.45522952	0.015339294
CTHRC1	collagen triple helix repeat containing 1	0.47890285	0.01084614
MXRA8	matrix remodeling associated 8	0.4874133	0.016108675

Open in a new tab

In order to encompass a broader spectrum of genes, those with a 1.5-fold or greater change were systematically cataloged, resulting in a total of 991 altered genes (S2 Table). Visual representation through heat maps effectively segregated sIBM and control myotubes, confirming the expected distinctions (Fig 2A). Gene Ontology (GO) term classification disclosed enrichment in biological processes (GO-BP) associated with skeletal muscle function, particularly in pathways such as muscle filament sliding and muscle contraction. Molecular function (GO-MF) analysis highlighted enrichment in actin filament binding and structural constituents of muscle (Fig 2B and 2C), reaffirming the specificity of changes linked to skeletal muscle cells.

To assess the dissimilarities in expression profiles between myotubes and muscle biopsies, RNA-seq analysis was performed on biopsy samples from individuals with sIBM (n = 3) and disease control (n = 4) samples (referred to as “biopsy” samples: S2 Table). A total of 901 genes exhibited more than a 1.5-fold variation in muscle biopsy samples. Notably, proteasome (prosome and macropain) subunit, beta type, 8 (PSMB8), a member of the interferon-2 pathway, was increased, consistent with previous analyses of biopsied muscle [31]. Other molecules in the interferon-2 pathway, including guanylate binding protein 1, interferon-inducible (GBP1), and GBP2 [31], were also elevated, along with upregulation of CCL13, interferon regulatory factor 8 (IRF8), CCR5, VCAM1, HLA-DRA, TYROBP, complement component 1, q subcomponent, B chain (C1QB), major histocompatibility complex class II, DR beta 1 (HLA-DRB1), CD74, and CXCL9 [8, 13, 14].

Then, a comparative analysis was conducted to determine the extent of the difference between the muscle biopsy and myotube samples (Fig 2D, S3 Table). Of the 53 extracted genes, 32 (60%) exhibited opposing directions of change in expression (e.g., increased in biopsy vs decreased in myotube). Among the commonly upregulated genes, transmembrane protein 8C (TMEM8C; also known as a myomaker, MYMK), myogenin (Myog), and ApoE were found, whereas metallothionein 2A (MT2A) was found among the downregulated genes (Fig 2E).

Among genes that were commonly altered in muscle biopsies and myotubes, molecules related to muscle differentiation and degeneration were examined at the protein level. MYMK is a myoblast fusion-associated molecule [32]. Deletion from myoblasts was reported to exacerbate symptoms in mouse models of muscular dystrophy [33]. The expression of MYMK was high in both myotubes and biopsy samples (Fig 3A and 3B). In immunostaining, the number of MYMK-positive myoblasts was higher in sIBM samples than in the control samples (Fig 3C).

Fig 3 — A. MYMK mRNA upregulation in sIBM myotubes. B. MYMK mRNA is upregulated in the sIBM biopsy muscle. (p-value = 0.00005, q-value = 0.002035). C. MYMK is found in the sIBM biopsy section. Scale bar, 10 μm. D. Quantification of the MYMK positive fibers (%).

The investigation extended to ApoE, known for its abnormal accumulation in sIBM and its potential role in muscle degenerative pathology [18–20]. High expression of ApoE in sIBM was found in the RNA-seq analysis of both myoblasts and muscle biopsies (Fig 4A and 4B). Immunostaining also showed high expression of ApoE in sIBM (Fig 4C), as shown previously [18–20]. Moreover, staining for amyloid oligomer A11 was enhanced in sIBM (Fig 4D).

Fig 4 — A. ApoE mRNA upregulation in sIBM myotubes. B. ApoE mRNA is upregulated in the sIBM biopsy muscle. (p-value = 0.00005, q-value = 0.002035). C. ApoE protein is upregulated in the sIBM biopsy section. Scale bar, 10 μm. D. Quantification of the ApoE positive fibers (%). E. Amyloid oligomer (A11) is upregulated in the sIBM biopsy section. Scale bar, 50 μm. F. Quantification of the Amyloid oligomer positive fibers (%).

The study then turned its attention to the quantification of ApoE proteins in myotubes. As anticipated, ApoE proteins were significantly increased in sIBM compared to control myotubes (Fig 5A and 5B, S1 Raw images). In addition, myogenin proteins were significantly increased in sIBM myotubes (Fig 5A and 5C).

Fig 5 — A. Representative blot of ApoE, GAPDH, and myogenin in sIBM and control myotubes. B. The protein level of ApoE is significantly increased in sIBM. P = 0.0025. Students’ t-test. C. The protein level of myogenin is significantly increased in sIBM. P = 0.0437. Students’ t-test.

Discussion

In this study, myotubes derived from sIBM-associated myoblasts were established, and a comprehensive RNA-seq analysis was conducted to delineate gene expression profiles specific to myotubes (Tables 2 and 3). By cross-referencing the RNA-seq results between the “myotube” and “biopsy” muscle, we could identify MYMK and ApoE, implicated in the myofiber-intrinsic contribution to the pathogenesis of sIBM (Fig 2, S3 Table).

A noteworthy observation was the inverse regulation of many genes upregulated in muscle biopsy, predominantly inflammatory genes, which exhibited significant downregulation in sIBM myotubes compared to control myotubes (S3 Table). Only 21 genes displayed shared directional changes in expression in both muscle biopsy and myotube samples, indicating a potential limitation in relying solely on myotubes to encapsulate the intricate pathology of sIBM (S3 Table).

Significantly, members of the interferon-2 pathway, such as PSMB8, GBP1, and GBP2, were elevated in biopsy samples, aligning with prior analyses of biopsied muscle [31]. This change is not observed in myotubes. This activation might represent a non-cell-autonomous mechanism contributing to muscle degeneration in sIBM. It may simply be expressed at low levels in myotubes but not reaching the threshold for detection, which is a limitation of our analysis in this study. Discriminating between cell types, such as through single-cell RNA-seq analysis, is a task for future research.

Given that changes in skeletal muscle- and myoblast-related molecules such as ApoE and myogenin (Figs 2, 4, and 5), which have been repeatedly noted in biopsies of sIBM previously [18–20, 30], were successfully identified in myotube and biopsied muscle, our analysis may be able to capture intrinsic changes in skeletal muscles in sIBM.

ApoE and lipoprotein receptors are also found in rimmed vacuole structure, suggesting an aberrant cholesterol metabolism in sIBM muscles [19, 20]. ApoE stimulates amyloid precursor protein transcription and amyloid beta secretion robustly in human neurons [34]. Amyloid beta-overexpressed mouse was used as the sIBM model [21]. The clarification of the mechanism by which ApoE is high in sIBM myotubes may lead to the control of ApoE-mediated abnormal protein accumulation and muscle degeneration. Additionally, it is possible that Amyloid beta overexpression might influence the characteristic KLRG1-T cells of inclusion body myositis [35] via the insulin-like growth factor signaling pathway [36] or immune modulation mechanisms [37]. Previously, we showed that the RNA-binding protein TDP-43 was localized from the nucleus to the cytoplasm in electric pulse stimulation culture [38]. Similar to ApoE, TDP-43 accumulates in the skeletal muscles in sIBM [39]. Patient-derived myotube cells may be useful for the study of the regulation of neurodegenerative disease-related proteins.

MYMK, a myomaker, is a well-conserved plasma membrane protein required for myoblast fusion to form multinucleated myotubes [32, 40]. Myogenin is also upregulated in sIBM myotubes [30]. Myogenin binds to the MYMK promoter and is required for the expression of MYMK and other genes essential for myocyte fusion [41]. Myogenin is also upregulated in sIBM muscle biopsy [30]. In denervation-induced muscle atrophy, myogenin plays both a regulator of muscle development and an inducer of neurogenic atrophy [42]. Given that enrichment analysis also captured changes in muscle contraction and development (Fig 2B and 2C), the triggering of muscle atrophy signaling and muscle differentiation via MYMK or myogenin may be involved in the pathogenesis of sIBM.

This study has several limitations. First, the cell culture condition might have changed the intrinsic gene expression in sIBM myotubes. Single-nuclei RNA-seq using human muscle biopsy could solve the intrinsic gene expression in myotubes in vivo. Second, SSC was defined as the control, although it was derived from a pathological joint in the RCT and therefore did not have normal function. In this study, we did not use inflammatory muscle disorders with an onset at a younger age, such as polymyositis, as controls in order to match the age range more effectively. Third, the quantity of sorted myoblasts was contingent on several factors, including the expression of antibody markers, the specific anatomical region of the muscle subjected to biopsy, and the uniformity and extent of digestion facilitated by collagenase. Lastly, the study was constrained by a limited number of samples.

In conclusion, the study elucidates the cell-autonomous profiles of sIBM-derived myotubes. ApoE and MYMK are commonly upregulated in both sIBM-derived myotubes and biopsy samples. This comprehensive catalog of gene expression changes stands as a valuable resource for future investigations into the pathogenesis of sIBM, with a specific focus on primary muscle degeneration.

Supporting information

S1 Fig. The expression of human muscle stem cell markers.

(TIF)

pone.0306021.s001.tif^{(9.2MB, tif)}

S1 Raw images. Protein levels of ApoE, myogenin and GAPDH in sIBM and control myotubes.

(PDF)

pone.0306021.s002.pdf^{(665.2KB, pdf)}

S1 Table. Unmapped reads.

(XLSX)

pone.0306021.s003.xlsx^{(10.4KB, xlsx)}

S2 Table. Dysregulated genes in sIBM myotube (vs SSC, >×1.5).

A total of 991 genes are listed.

(XLSX)

pone.0306021.s004.xlsx^{(58.3KB, xlsx)}

S3 Table. Dysregulated genes in sIBM biopsy samples (vs disease control, >×1.5).

A total of 901 genes are listed.

(XLSX)

pone.0306021.s005.xlsx^{(56.3KB, xlsx)}

S4 Table. Common dysregulated genes in sIBM myotube and biopsy samples.

A total of 53 genes are listed. Although genes are listed, most of the upregulated genes in muscle biopsy samples are downregulated in myotubes.

(XLSX)

pone.0306021.s006.xlsx^{(14.2KB, xlsx)}

Acknowledgments

We thank Naoko Shimakura, Akiko Machii, Mai Kakinuma, and Hinako Shigihara (Tohoku University, Japan) for general technical support and Enago for the English language review (www.enago.jp). We also thank Ayami Otsuki for the cell culture and Dr. Maki Tateyama (National Hospital Organization Iwate Hospital, Japan) for useful technical advice and discussions.

Data Availability

The accession number for the RNA-seq data reported in this paper is DDBJ (DNA DataBank of Japan), https://ddbj.nig.ac.jp/resource/sra-submission/DRA017123, DRA accession number: DRA017123.

Funding Statement

This research was partially supported by Intramural Research Grants 29-4 and 2-5 for Neurological and Psychiatric Disorders provided to M.A. from the National Center of Neurology and Psychiatry of Japan; the Practical Research Project for Rare/Diseases (20dk0310086) provided to M.A. and Moonshot R&D Program (JPMJMS 23zf0127001h0003) to T.A. from the Japan Agency for Medical Research and Development (AMED); Grants-in-Aid for Research on Rare and Intractable Diseases (H29-nanchitou(nan)-ippan-030 and 20CF1036) provided to M.A. from the Ministry of Health, Labor and Welfare of Japan; a Grant-in-Aid for Challenging Exploratory Research (20K21563) provided to M.A. and N.S., Scientific Research C (18K07519) provided to N.S., from the Japanese Ministry of Education, Culture, Sports, Science and Technology. This research was also supported by the Cooperative Research Project Program of the Joint Usage/Research Center at the Institute of Development, Aging and Cancer, Tohoku University.

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PONE-D-24-02730Sporadic inclusion body myositis-derived myotube culture revealed muscle cell-autonomous expression profilesPLOS ONE

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Reviewer #1: A straightforward study examining the similarities between myotubes derived from myoblasts from inclusion body myositis patients and age matched controls. These samples are assessed by RNA-seq and compared to RNA-seq data from whole muscle biopsies. Overall, the study is interesting but several areas would strengthen the conclusions and allows for more complete interpretation of the data.

Methods: Central to this study is the isolation of myogenic precursor cells from human muscle biopsies. The protocol used (FACS sorting) relies heavily on negative sorts to isolate myoblasts (MuSCs?) and only CD56 is used as a positive sort. To increase confidence, the isolated cells should also be subjected to a positive sort, or in this case, since the RNA-seq analysis is complete, that validation of the purity of the cells used for differentiation be used with accepted markers for human MuScs (eg. Integrin alpha 7, m-cadherin, CD82).

Figure 1B-E. Overlay of the DAPI and desmin stain is critical to appreciate the % of cells that have not differentiated. While this appears to be high for both conditions, a calculation of the differentiation index would also help appreciate the level of contamination from reserve cells and the expected variability from sample to sample and experiment to experiment. This has an impact on the downstream analysis and the interpretation of the findings.

Figure 2. For the RNA-seq analysis, it would be beneficial to include the FDR cut-offs used for significance in the text. Changes in the expression of factors associated with differentiation and myofiber maturity/contraction can be related to differences in the efficiency of differentiation between samples.

For the comparative analysis, it is not surprising that genes that are uniquely expressed in myofibers are also commonly regulated in whole muscle samples. More interesting however, is the massive number of genes oppositely regulated. No further analysis is provided here, but would be very useful in terms of understanding the origins. Was a similar analysis done for controls (or were the DEGs determined as relative to controls?). It would be interesting to see how divergent the control myotubes are from the healthy whole muscle, as a way to infer differences that the microenvironment contributes.

For the comparison between myotubes generated in culture and whole muscle biopsy samples, The gene name for Tmem8c is actually MYMK and this should be changed throughout.

Figure 3. The text says that the levels were verified at the protein level, however FPKM are shown and no quantification over the patient samples are provided for the immunostained images. Quantifications are essential to validate the conclusions.

Figure 4. Similar comments to Figure 3.

Discussion:

Line 323. I do not think the word pathogenesis applied to the myotubes in culture. I appreciate that you mean a myofiber-intrinsic contribution to the pathogenesis of the disease, but this is not clear as written.

This statement (lines 332-336) “The examination of muscle biopsies suggested altered gene expression in lymphocytes and other immunopathological conditions, phenomena not mirrored in myotube samples.” Is not supported by the data shown.

The statement in lines 337-340 is also unclear as to where the findings come from (as related to SASP). Please clarify.

Minor comments: Care should be taken to use the appropriate gene nomenclature for humans throughout to avoid confusion with mouse genes or protein names.

Reviewer #2: Suzuki et al. present an interesting finding regarding the pathological mechanism(s) involved in sIBM. Previous findings have failed to define the pathology as autoimmune or degenerative, not having determined whether the pathology observed is primarily due to intrinsic or extrinsic forces. In their study the authors confront the gene expression profile using RNA-seq between sIBM biopsy samples and controls as well as with myotubes derived from myoblasts isolated from control and sIBM biopsies. In such a manner, the study is able to differentiate between gene expression profiles of sIBM biopsies (due both to intrinsic and extrinsic forces), and gene expression profiles of in vitro differentiated sIBM-derived myotubes (due to intrinsic forces). The data are interesting and find similar results to previous reports. What is missing is a full consideration of the findings.

Major comments:

1. Figure 1, please show the merged image of DAPI and desmin.

2. As sIBM leads to muscle death and atrophy, it is important to known if any difference was observed in the differentiation potential/rate and viability between controls and sIBM biopsy-derived myoblasts.

3. Data from myotubes suggests a potential alteration of the insulin growth factor response and cellular adhesion in sIBM. How does this fit in with previous findings in the field?

4. In discussing differences between data in Supplementary Table 2 and Supplementary Table 3, the authors observe the absence of immunopathological gene expression (lines 333-341) in myotubes and suggest that some phenotypic findings may be linked to STING and non-cell-autonomous mechanisms. The authors should be careful here with this interpretation. First, there is more than STING to consider; second, data in Supplemental Table 2 could suggest a defective type I interferon response; and third, the authors used a cut-off for choosing which genes to include in their analysis, but it should be noted that in almost all cases, the ratio of gene expression of common genes between sIBM-derived myotubes/control versus sIGM biopsy/control is always decreased. therefore some changes seen in the biopsy samples may have been below the threshold for consideration in the myotubes, but none-the-less still present.

5. The authors focus then on ApoE, TMEM8C and myogenin. The pathophysiological role that upregulation of these proteins has in sIBM is difficult to determine. TMEM8C and myogenin should, at face value, favor muscle development. Likewise, the role of ApoE is difficult to determine due to its varying immunomodulatory roles, including T cell suppression.

6. From the RNA-seq data, the authors should state the number of reads that could not be matched for each experiment. Additionally, in regard to the 53 genes common to myotubes and biopsies, the authors should look at the sequence and exon usage to determine if any of these common genes contain mutations or are potentially alternatively spliced between control and sIBM, including ApoE and TMEM8C (use of a monoclonal antibody may not necessarily catch all isoforms).

Minor comments:

1. Please define the supplier DBS, line 221.

2. For the lysis buffer on line 233, add "(RIPA)" between "radio-immunoprecipitation" and "buffer".

3. In Supplemental Table 3 it might be beneficial to organize the table as those genes that commonly increase in sIBM versus those that increase in biopsy but decrease in myotubes or vice versa.

**********

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PLoS One. 2024 Aug 1;19(8):e0306021. doi: 10.1371/journal.pone.0306021.r002

Author response to Decision Letter 0

1 Jun 2024

＊＊＊＊＊＊＊＊＊＊＊＊＊＊＊

Point-to-point response to Reviewers’ comments:

Reviewer #1: A straightforward study examining the similarities between myotubes derived from myoblasts from inclusion body myositis patients and age matched controls. These samples are assessed by RNA-seq and compared to RNA-seq data from whole muscle biopsies. Overall, the study is interesting but several areas would strengthen the conclusions and allows for more complete interpretation of the data.

Thank you for your valuable insights. As you mentioned, the myoblasts in this study were purified using FACS sorting, with negative sorting for CD45, CD31, and CD11b. We have included a figure depicting the gating strategy we previously reported as below (Koide et al.). In this strategy, we consistently create negative controls and set gating for CD56 positivity to accurately select myogenic precursors. Additionally, the high purity of differentiated myotubes is demonstrated in the revised Figure 1B-E as mentioned later.

Ref: Koide et al. Tohoku J Exp Med 2018

Furthermore, in response to reviewer comments, we analyzed the expression levels of muscle markers in myotubes using RNA-seq (S1 Fig). As suggested, the expression of human muscle stem cell markers such as Integrin alpha 7 (ITGA7), m-cadherin (CDH15), and CD82 was found to be high. Conversely, the expression of inflammatory, chemokine, and mesodermal markers such as Interleukin-1a (IL1A), C-C chemokine receptor type 2 (CCR2), and SRY-related HMG-box (SOX)10 was not detected.

These data further support the assertion that the cells isolated in this study are human myoblasts.

In the Results section, the following sentence has been added: “In both control and sIBM-derived myotubes, the expression of human muscle stem cell markers such as Integrin alpha 7 (ITGA7), m-cadherin (CDH15), and CD82 was observed to be high (S1 Fig).”

For Figures 1B-E, it's notable that even instances with low fluorescence intensity are positive for Desmin. Following reviewer’s recommendation, including overlay images, we labeled them as Figure 1B-G. Quantification revealed that 95-98% of nuclei overlapped with Desmin (new Figure 1H). Both Control and sIBM samples exhibited similar positivity rates, indicating minimal impact on differentiation efficiency. This positivity rate aligns with previous reports (Oikawa et al.).

We added the sentences in Result section as below. “When quantified, it was determined that 95-98% of the nuclei exhibited colocalization with Desmin, as depicted in Figure 1H.”

The False Discovery Rate (FDR) cutoff value was set at 0.05.　As we mentioned above, we analyzed the expression levels of muscle markers in myotubes using RNA-seq (new S1 Fig). As suggested, the expression of human muscle stem cell markers such as Integrin alpha 7 (ITGA7), m-cadherin (CDH15), and CD82 was found to be high. Conversely, the expression of inflammatory, chemokine, and mesodermal markers such as Interleukin-1a (IL1A), C-C chemokine receptor type 2 (CCR2), and SRY-related HMG-box (SOX)10 was not detected. These data further support the assertion that the cells isolated in this study are human myoblasts.

For the comparison between myotubes generated in culture and whole muscle biopsy samples, The gene name for Tmem8c is actually MYMK and this should be changed throughout.

Thank you for highlighting these important points. As you mentioned, the observation of genes expressed in myofibers but showing opposite expression patterns in patient muscle tissue suggests the involvement of different cell types. Given the pathology of sIBM involving inflammatory cell infiltration, fibrosis, and adipose tissues, potential confounding effects of non-muscle cells in expression data analysis are expected. We have addressed this point in the Discussion section.

While it is crucial to understand the extent of differences between Control Myotubes and healthy muscle, it was challenging to address this in the current study as Disease control Whole muscle samples were used. However, we acknowledge the importance of this aspect and consider it as a future direction, particularly through single-cell analysis to dissect the cellular resources of expression changes.

We added the description in the discussion session as follows: “This change is not observed in myotubes. This activation might represent a non-cell-autonomous mechanism contributing to muscle degeneration in sIBM. It may simply be expressed at low levels in myotubes but not reaching the threshold for detection, which is a limitation of our analysis in this study. Discriminating between cell types, such as through single-cell RNA-seq analysis, is a task for future research.”

Furthermore, TMEM8C has been renamed as MYMK, as indicated in the revised figure and text.

The reviewer’s comments are absolutely valid. We have re-quantified the immunostaining and created a graph. A statistically significant difference was found between the control and sIBM (p=0.0358). The number of muscle fibers expressing TMEM8C/MYMK is shown as a percentage. We have also added the quantitative data to Figure 3D.

Figure 4. Similar comments to Figure 3.

Thank you for pointing this out. We have also quantified the ApoE and amyloid oligomer, and the results have been added to Figure 4. Significant differences were found in both cases.

Discussion:

Thank you for pointing out that the term 'pathogenesis' may not be appropriate in the context of myotubes in culture. Following your suggestion, I have revised the phrase to 'myofiber-intrinsic contribution to the pathogenesis of the disease' for clarity.

The statement in lines 337-340 is also unclear as to where the findings come from (as related to SASP). Please clarify.

The description regarding STING did not extend beyond speculation. As it exceeded the scope of this paper, it has been removed. The points raised by the reviewer have been addressed as limitations, and the paragraph has been revised as follows:

“Significantly, members of the interferon-2 pathway, such as PSMB8, GBP1, and GBP2, were elevated in biopsy samples, aligning with prior analyses of biopsied muscle31. This change is not observed in myotubes. This activation might represent a non-cell-autonomous mechanism contributing to muscle degeneration in sIBM. It may simply be expressed at low levels in myotubes but not reaching the threshold for detection, which is a limitation of our analysis in this study. Discriminating between cell types, such as through single-cell RNA-seq analysis, is a task for future research.”

Minor comments: Care should be taken to use the appropriate gene nomenclature for humans throughout to avoid confusion with mouse genes or protein names.

I capitalized the names of human genes.

Reviewer #2: Suzuki et al. present an interesting finding regarding the pathological mechanism(s) involved in sIBM. Previous findings have failed to define the pathology as autoimmune or degenerative, not having determined whether the pathology observed is primarily due to intrinsic or extrinsic forces. In their study the authors confront the gene expression profile using RNA-seq between sIBM biopsy samples and controls as well as with myotubes derived from myoblasts isolated from control and sIBM biopsies. In such a manner, the study is able to differentiate between gene expression profiles of sIBM biopsies (due both to intrinsic and extrinsic forces), and gene expression profiles of in vitro differentiated sIBM-derived myotubes (due to intrinsic forces). The data are interesting and find similar results to previous reports. What is missing is a full consideration of the findings.

Major comments:

1. Figure 1, please show the merged image of DAPI and desmin.

We added the sentences in Result section as below. “When quantified, it was determined that 95-98% of the nuclei exhibited colocalization with Desmin, as depicted in Figure 1H.”

Thank you for your valuable insights. The high purity of differentiated myotubes is demonstrated in the revised Figure 1B-E. Furthermore, in response to reviewer1’s comments, we analyzed the expression levels of muscle markers in myotubes using RNA-seq (Supplemental Fig). As suggested, the expression of human muscle stem cell markers such as Integrin alpha 7 (ITGA7), m-cadherin (CDH15), and CD82 was found to be high. Conversely, the expression of inflammatory, chemokine, and mesodermal markers such as Interleukin-1a (IL1A), C-C chemokine receptor type 2 (CCR2), and SRY-related HMG-box (SOX)10 was not detected.

These data further support the assertion that the cells isolated in this study are human myoblasts.

In the Results section, the following sentence has been added: In both control and sIBM-derived myotubes, the expression of human muscle stem cell markers such as Integrin alpha 7 (ITGA7), m-cadherin (CDH15), and CD82 was observed to be high (S1 Fig).

If stressors such as BSO are not applied, the survival rate of sIBM myoblasts does not differ from that of the control, as reported by Oikawa et al.

Ref: Oikawa Y, et al. PLoS One. 2020;15:e0231064.

3. Data from myotubes suggests a potential alteration of the insulin growth factor response and cellular adhesion in sIBM. How does this fit in with previous findings in the field?

Thank you for highlighting this important point. Regarding insulin-like growth factor (IGF), Broccolini et al.'s pathological work indicates increased expression in sIBM. They also conducted experiments where normal primary muscle cultures were stimulated for 24 hours with the Amyloid beta peptide, which corresponds to the biologically active domain of Amyloid beta. In their discussion, they propose that IGF-I overexpression may represent a reactive response to Amyloid beta toxicity. This is intriguing in the context of our observed increase in A beta expression.

Added to the Discussion section:

“Additionally, it is possible that Amyloid beta overexpression might influence the characteristic KLRG1-T cells of inclusion body myositis via the insulin-like growth factor signaling pathway or immune modulation mechanisms.”

Ref: Broccolini A, et al. J Neuropathol Exp Neurol. 2004;63:650-9.

Ref: Laskowitz DT, et al. J Lipid Res. 2000;41:613-20.

Ref: Goyal NA, et al. Neurology. 2022;98:e1374-e1383.

The observed changes in TMEM8C and myogenin indicate muscle development and likely reflect the muscle damage and repair processes in sIBM. It is hypothesized that there may be mechanisms disrupting the remodeling process, resulting in impaired muscle regeneration. Moreover, ApoE plays immunomodulatory roles, including T cell suppression, and its abnormalities could potentially affect KLRG1-positive T cells. These points remain speculative, but we have mentioned their relationship with Aβ briefly in the text, considering them important topics for future analysis.

Added to

PLoS One. doi: 10.1371/journal.pone.0306021.r003

Decision Letter 1

Keisuke Hitachi

11 Jun 2024

Sporadic inclusion body myositis-derived myotube culture revealed muscle cell-autonomous expression profiles

PONE-D-24-02730R1

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6. Review Comments to the Author

Reviewer #1: The authors have carefully and completely addressed my comments from the first round of review. The revised manuscript better discusses limitations of the experimental approach and also provides additional information to the reader which helps interpretation of the data sets.

Reviewer #2: (No Response)

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PLoS One. doi: 10.1371/journal.pone.0306021.r004

Acceptance letter

Keisuke Hitachi

27 Jun 2024

PONE-D-24-02730R1

PLOS ONE

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. The expression of human muscle stem cell markers.

(TIF)

pone.0306021.s001.tif^{(9.2MB, tif)}

S1 Raw images. Protein levels of ApoE, myogenin and GAPDH in sIBM and control myotubes.

(PDF)

pone.0306021.s002.pdf^{(665.2KB, pdf)}

S1 Table. Unmapped reads.

(XLSX)

pone.0306021.s003.xlsx^{(10.4KB, xlsx)}

S2 Table. Dysregulated genes in sIBM myotube (vs SSC, >×1.5).

A total of 991 genes are listed.

(XLSX)

pone.0306021.s004.xlsx^{(58.3KB, xlsx)}

S3 Table. Dysregulated genes in sIBM biopsy samples (vs disease control, >×1.5).

A total of 901 genes are listed.

(XLSX)

pone.0306021.s005.xlsx^{(56.3KB, xlsx)}

S4 Table. Common dysregulated genes in sIBM myotube and biopsy samples.

A total of 53 genes are listed. Although genes are listed, most of the upregulated genes in muscle biopsy samples are downregulated in myotubes.

(XLSX)

pone.0306021.s006.xlsx^{(14.2KB, xlsx)}

Data Availability Statement

The accession number for the RNA-seq data reported in this paper is DDBJ (DNA DataBank of Japan), https://ddbj.nig.ac.jp/resource/sra-submission/DRA017123, DRA accession number: DRA017123.

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PERMALINK

Sporadic inclusion body myositis-derived myotube culture revealed muscle cell-autonomous expression profiles

Naoki Suzuki

Makoto Kanzaki

Masashi Koide

Rumiko Izumi

Ryo Fujita

Tadahisa Takahashi

Kazumi Ogawa

Yutaka Yabe

Masahiro Tsuchiya

Masako Suzuki

Ryuhei Harada

Akiyuki Ohno

Hiroya Ono

Naoko Nakamura

Kensuke Ikeda

Hitoshi Warita

Shion Osana

Yoshitsugu Oikawa

Takafumi Toyohara

Takaaki Abe

Muliang Rui

Satoru Ebihara

Ryoichi Nagatomi

Yoshihiro Hagiwara

Masashi Aoki

Roles

Abstract

Introduction

Materials and methods

Study population

Sample collection from patients with sIBM

Table 1. Characteristics of patients with sporadic inclusion body myositis.

Primary myoblast isolation

Cell culture

RNA extraction and sequencing analysis

Immunohistochemistry and immunocytochemistry

Immunoblotting

Statistical analysis

Results

Fig 1. Myotubes derived from patient muscle biopsy samples.

Fig 2. Intrinsic cell-autonomous characterization of myotubes derived from sIBM.

Table 2. Upregulated genes in sIBM myotube (vs control, >×2, p < 0.05, Student’s t-test (equal variance)).

Table 3. Downregulated genes in sIBM myotube (vs SSC, >×2, p < 0.05, Student’s t-test (equal variance)).

Fig 3. Expression of MYMK in both myotubes and sIBM biopsy sections.

Fig 4. Expression of ApoE in sIBM biopsy sections.

Fig 5. Protein levels of ApoE and myogenin in sIBM myotubes.

Discussion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Keisuke Hitachi

Roles

Author response to Decision Letter 0

Decision Letter 1

Keisuke Hitachi

Roles

Acceptance letter

Keisuke Hitachi

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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