Impact of short- and long-term electrically induced muscle exercise on gene signaling pathways, gene expression, and PGC1a methylation in men with spinal cord injury

Abstract

Exercise attenuates the development of chronic noncommunicable diseases (NCDs). Gene signaling pathway analysis offers an opportunity to discover if electrically induced muscle exercise regulates key pathways among people living with spinal cord injury (SCI). We examined short-term and long-term durations of electrically induced skeletal muscle exercise on complex gene signaling pathways, specific gene regulation, and epigenetic tagging of PGC1a, a major transcription factor in skeletal muscle of men with SCI. After short- or long-term electrically induced exercise training, participants underwent biopsies of the trained and untrained muscles. RNA was hybridized to an exon microarray and analyzed by a gene set enrichment analysis. We discovered that long-term exercise training regulated the Reactome gene sets for metabolism (38 gene sets), cell cycle (36 gene sets), disease (27 gene sets), gene expression and transcription (22 gene sets), organelle biogenesis (4 gene sets), cellular response to stimuli (8 gene sets), immune system (8 gene sets), vesicle-mediated transport (4 gene sets), and transport of small molecules (3 gene sets). Specific gene expression included: oxidative catabolism of glucose including PDHB (P < 0.001), PDHX (P < 0.001), MPC1 (P < 0.009), and MPC2 (P < 0.007); Oxidative phosphorylation genes including SDHA (P < 0.006), SDHB (P < 0.001), NDUFB1 (P < 0.002), NDUFA2 (P < 0.001); transcription genes including PGC1α (P < 0.030) and PRKAB2 (P < 0.011); hypertrophy gene MSTN (P < 0.001); and the myokine generating FNDC5 gene (P < 0.008). Long-term electrically induced exercise demethylated the major transcription factor PGC1a. Taken together, these findings support that long-term electrically induced muscle activity regulates key pathways associated with muscle health and systemic metabolism.

Keywords: epigenomic; exercise; genomic; muscle; paralysis.

Conflict of interest statement

No conflicts of interest, financial or otherwise, are declared by the authors.

Figures

Fig. 1.

Heat maps for the top 50 increased and top 50 decreased genes as determined by their enrichment score from gene set enrichment analysis (GSEA) for the short- and long-term training cohorts. The enrichment score is created from a combination of the P value statistic for the fold-change between the exercised and non-exercised limbs and the rank order expression intensity for each phenotype. The heat map represents the relative gene expression intensity for each subject represented as colors (red and blue). Red indicates a relative increased level of expression; while blue indicates a relative decreased level of expression for a given gene. The darker the color (red or blue), the larger the relative increase or decrease in gene expression, respectively. Among the top 50 genes the fold-changes varied across cohorts with a maximum of near 50 for the trained limb relative to the control limb, and a decrease for the control limb relative to the trained limb representing decreased gene expression (blue).

Fig. 2.

A: base connectivity map for the 1,925 gene sets used for the gene set enrichment analysis (GSEA). Each node represents a gene set pathway defined within the Reactome Knowledgebase, which defines various biological processes categorized into 26 primary families, as indicated by node color. The size of each node depends on the number of genes defined within the gene set; therefore, larger nodes have more genes defined compared with the smaller nodes. Nodes with direct relationships are connected by a black line. B: the GSEA results mapped the connectivity map for the people in the long-term exercise training cohort. Only the 223 gene set pathways that met the <25% false discovery rate (FDR) cutoff are visible. The darkness of the red border color for each node indicates whether the significance of upregulation detected in the exercise limb compared with the nonexercised limb. Node transparency indicates the relative FDR from the GSEA; therefore, darker nodes were more significantly regulated than lighter nodes. Nodes that did not meet an FDR of 25% are fully transparent, but their relative position in space and connections to neighboring nodes are preserved. C: there were 223 gene sets found to be significantly regulated for people in the long-term exercise training cohort from 16 of the 26 gene families. Of note is that 39, 13, and 8 were gene sets associated with the Metabolism, Metabolism of Proteins, and Metabolism of RNA families. Additionally, the Gene Expression and Transcription and Cell Cycle families had 34 and 23 pathways significantly upregulated with long-term exercise training.

Fig. 3.

Gene expression for genes with important transcriptional regulatory activity in skeletal muscle (PGC1α), regulation of muscle atrophy (MSTN), and myokine signaling to systemic tissues (FNDC5 and CTSB). The expression in the long-term exercise training cohort was significantly higher compared with those in the short-term exercise training cohort and at baseline (untrained limb) for PGC1α, FNDC5, and PRKAB2. Meanwhile, MSTN was significantly decreased after long-term exercise training compared with those in the short-term exercise training cohort and at baseline (untrained limb). *P value < 0.05 from a mixed-model ANOVA.

Fig. 4.

Gene expression for genes important for glucose metabolism (PDHB and PDHX) and the transfer of pyruvate from the cytosol to the mitochondria for continued oxidation within the tricarboxylic acid cycle and oxidative phosphorylation pathways (MPC1 and MPC2). The expression in the long-term exercise training cohort was significantly higher compared with those in the short-term exercise training cohort and at baseline (untrained limb) for PDHB, PDHX, MPC1, and MPC2. *P value < 0.05 from a mixed model ANOVA.

Fig. 5.

Gene expression for genes important for tricarboxylic acid cycle (SDHA and SDHB) and oxidative phosphorylation (NDUFA2 and NDUFB1). The expression in the long-term exercise training cohort was significantly higher compared with those in the short-term exercise training cohort and at baseline (untrained limb) for SDHA, SDHB, NDUFA2, and NDUFB1. *P value < 0.05 from a mixed-model ANOVA.

Fig. 6.

The median demethylation after long-term exercise training across all CpG sites for the potent transcription regulator PGC1α in people with SCI at baseline and after long-term exercise training using electrical muscle stimulation. *P value < 0.05 from a paired t test.