Multi-omics analysis of sarcospan overexpression in mdx skeletal muscle reveals compensatory remodeling of cytoskeleton-matrix interactions that promote mechanotransduction pathways - PubMed (original) (raw)

doi: 10.1186/s13395-022-00311-x.

Kristen M Stearns-Reider # 1 2, Hafsa Mamsa # 1, Pranav Kannan 1, Mohammad Hossein Afsharinia 1, Cynthia Shu 1, Elizabeth M Gibbs 1, Kara M Shin 1, Yerbol Z Kurmangaliyev 3, Lauren R Schmitt 4, Kirk C Hansen 4, Rachelle H Crosbie 5 6 7 8

Affiliations

Multi-omics analysis of sarcospan overexpression in mdx skeletal muscle reveals compensatory remodeling of cytoskeleton-matrix interactions that promote mechanotransduction pathways

Jackie L McCourt et al. Skelet Muscle. 2023.

Abstract

Background: The dystrophin-glycoprotein complex (DGC) is a critical adhesion complex of the muscle cell membrane, providing a mechanical link between the extracellular matrix (ECM) and the cortical cytoskeleton that stabilizes the sarcolemma during repeated muscle contractions. One integral component of the DGC is the transmembrane protein, sarcospan (SSPN). Overexpression of SSPN in the skeletal muscle of mdx mice (murine model of DMD) restores muscle fiber attachment to the ECM in part through an associated increase in utrophin and integrin adhesion complexes at the cell membrane, protecting the muscle from contraction-induced injury. In this study, we utilized transcriptomic and ECM protein-optimized proteomics data sets from wild-type, mdx, and mdx transgenic (mdxTG) skeletal muscle tissues to identify pathways and proteins driving the compensatory action of SSPN overexpression.

Methods: The tibialis anterior and quadriceps muscles were isolated from wild-type, mdx, and mdxTG mice and subjected to bulk RNA-Seq and global proteomics analysis using methods to enhance capture of ECM proteins. Data sets were further analyzed through the ingenuity pathway analysis (QIAGEN) and integrative gene set enrichment to identify candidate networks, signaling pathways, and upstream regulators.

Results: Through our multi-omics approach, we identified 3 classes of differentially expressed genes and proteins in mdxTG muscle, including those that were (1) unrestored (significantly different from wild type, but not from mdx), (2) restored (significantly different from mdx, but not from wild type), and (3) compensatory (significantly different from both wild type and mdx). We identified signaling pathways that may contribute to the rescue phenotype, most notably cytoskeleton and ECM organization pathways. ECM-optimized proteomics revealed an increased abundance of collagens II, V, and XI, along with β-spectrin in mdxTG samples. Using ingenuity pathway analysis, we identified upstream regulators that are computationally predicted to drive compensatory changes, revealing a possible mechanism of SSPN rescue through a rewiring of cell-ECM bidirectional communication. We found that SSPN overexpression results in upregulation of key signaling molecules associated with regulation of cytoskeleton organization and mechanotransduction, including Yap1, Sox9, Rho, RAC, and Wnt.

Conclusions: Our findings indicate that SSPN overexpression rescues dystrophin deficiency partially through mechanotransduction signaling cascades mediated through components of the ECM and the cortical cytoskeleton.

Keywords: Duchenne muscular dystrophy; Dystroglycan; Dystrophin; Extracellular matrix; Sarcospan.

© 2022. The Author(s).

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1

Fig. 1

Overview of RNA sequencing and mass spectrometry reveals distinct transcriptomic and proteomic profiles of SSPN overexpression rescue. a Principal component analysis (PCA) of RNA sequencing data in wild type (WT, n = 5), mdx (n = 4), and mSSPN transgenic (_mdx_TG, n = 4) tibialis anterior muscle at 12 weeks of age. b Heat map of DEGs. c PCA of mass spectrometry data from WT (n = 5), mdx (n = 5), and hSSPN transgenic (_mdx_TG, n = 5) quadriceps muscle at 20 weeks of age. d Heat map of differentially expressed proteins (DEPs). e Overlap of Gene Ontology (GO) terms enriched in WT vs _mdx_TG in transcriptomics vs proteomics data using PANTHER GO analysis platform

Fig. 2

Fig. 2

SSPN overexpression results in compensatory upregulation of ECM and actin cytoskeleton genes. Heat maps of GO-term curated ECM genes (a) and actin cytoskeleton genes (b) from RNA sequencing data each with restored, unrestored, and compensatory expression patterns in the _mdx_TG muscle. Expanded heat map insets emphasize that compensatory expression patterns are overwhelmingly from upregulated genes in the _mdx_TG muscle

Fig. 3

Fig. 3

Compensatory changes in functional classes of ECM and cytoskeletal proteins in _mdx_TG muscle. a Graph of the abundance of ECM proteins in 8 primary categories relative to WT. b Graph of the abundance of cytoskeletal proteins in 9 primary categories relative to WT (*p < 0.05 compared to WT, #p < 0.05 compared to mdx by unpaired _t_-test. By category, _mdx_TG muscle had compensatory expression (both significantly different from WT and mdx) of matricellular, ECM regulator, basement membrane, actins/microfilaments, actin-associated, myosins, and sarcomere-associated proteins

Fig. 4

Fig. 4

Upregulation of ECM regulators, fibrillar collagens, and spectrins in _mdx_TG muscle. Relative protein expression of ECM regulators (a), fibrillar collagens (b), spectrins (c), and actins/microfilaments (d) (*p < 0.05 compared to WT, #p < 0.05 compared to mdx by unpaired _t_-test)

Fig. 5

Fig. 5

Activated and inhibited upstream regulators identified in wild-type, mdx and _mdx_TG muscle through ingenuity pathway analysis. Ingenuity pathway analysis (IPA) of RNA sequencing data (a) and mass spectrometry data (b) identifying the top 10 upstream regulators that are activated (_z_-score, red bars) or inhibited (_z_-score, blue bars) with −log _p_-values overlaid in black. Comparisons include WT vs mdx (left graphs), WT vs _mdx_TG (middle graphs), and mdx vs _mdx_TG (right graphs)

Fig. 6

Fig. 6

Integrated gene set enrichment analysis identifies differential expression of mechanosignaling pathways in _mdx_TG. To develop an integrated model of overlapping signaling networks driving rescue of the _mdx_TG skeletal muscle, we combined transcripts (diamonds) and proteins (ovals) that were differentially expressed between mdx and _mdx_TG tissue and performed gene set enrichment analysis. Compensatory changes are in pink, restored changes are in green, and uncategorized changes are in gray. The gene set enrichment analysis highlights changes in Rho, Rac, Wnt, and integrin signaling in addition to cell adhesion and response to mechanical stimulus

Fig. 7

Fig. 7

Validation of signaling and mechanosensitive pathways increased in _mdx_TG muscle. Indirect immunofluorescence analysis and quantification of 12-week-old mouse quadriceps using antibodies against (a) collagen II (Col II) and collagen V (Col V), (b)_β_-spectrin (Sptbn1), (c) yes-associated protein 1 (Yap1) and SRY-Box transcription factor 9 (Sox9) showing increased abundance in _mdx_TG relative to both WT and mdx. Sox9 is expressed at the neuromuscular junction shown by co-localization with α-bungarotoxin (α-BgTx). Statistical analyses were performed by one-way ANOVA with Tukey’s multiple comparison tests, n = 3–4 biological replicates per genotype, data represented as +/− SEM (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001). Scale bar = 100 μm

Fig. 8

Fig. 8

SSPN overexpression rewires ECM-cell communication. Schematic summarizing ECM and cytoskeletal changes in RNA sequencing and proteomic data sets. Changes in gene or protein expression are represented by color according to the key, indicating compensatory upregulation of many ECM and cytoskeletal molecules with downstream signaling effects (in purple). The _x_- and _y_-axes in the color key correspond to _mdx_TG relative to WT and _mdx_TG relative to mdx, respectively

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