Skeletal muscle remodeling

Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9148, USA.
Current Opinion in Rheumatology (Impact Factor: 4.89). 12/2007; 19(6):542-9. DOI: 10.1097/BOR.0b013e3282efb761
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In skeletal muscle, environmental demands activate signal transduction pathways that ultimately promote adaptive changes in myofiber cytoarchitecture and protein composition. Recent advances in determining the factors involved in these signal transduction pathways provide insight into possible therapeutic methods to remodel skeletal muscle.
Advances in genetic engineering have allowed the introduction or depletion of factors within the myofiber, facilitating the evaluation of signaling factors during muscle remodeling. Using transgenic mouse models, activation of specific signaling pathways promoted type I oxidative myofibers, increased the fatigue resistance of muscle, increased skeletal muscle mass and ameliorated muscle injury in myopathic mouse models. Moreover, new technologies are being used to generate global gene and protein expression profiles to identify new factors involved in skeletal muscle remodeling. Finally, small RNAs, microRNAs, are emerging as powerful regulators of gene expression in most tissues, including skeletal muscle. Recent findings predict that targeted delivery of miRNAs will specifically manipulate genes and if used therapeutically will revolutionize clinical medicine.
Developing drugs to target signaling pathways associated with remodeling myofibers provides a possible therapeutic approach to combat skeletal muscle disease. In addition, genome-wide technologies can identify new biomarkers capable of diagnosing myopathies and determine a patient's response to therapy. Furthermore, therapeutic strategies are being designed to target microRNAs in anticipation of blocking gene repression correlated with muscle pathology.

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Available from: Matthew J Potthoff, Aug 08, 2014
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    • "The actions of HATs and HDACs are intimately involved in the mechanisms of cardiac and skeletal muscle gene expression [7-10]. A number of studies have demonstrated a positive therapeutic potential of HDACIs in animal models of cardiac hypertrophy. "
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    ABSTRACT: Background We have shown previously that pan-HDAC inhibitors (HDACIs) m-carboxycinnamic acid bis-hydroxamide (CBHA) and trichostatin A (TSA) attenuated cardiac hypertrophy in BALB/c mice by inducing hyper-acetylation of cardiac chromatin that was accompanied by suppression of pro-inflammatory gene networks. However, it was not feasible to determine the precise contribution of the myocytes- and non-myocytes to HDACI-induced gene expression in the intact heart. Therefore, the current study was undertaken with a primary goal of elucidating temporal changes in the transcriptomes of cardiac myocytes exposed to CBHA and TSA. Results We incubated H9c2 cardiac myocytes in growth medium containing either of the two HDACIs for 6h and 24h and analyzed changes in gene expression using Illumina microarrays. H9c2 cells exposed to TSA for 6h and 24h led to differential expression of 468 and 231 genes, respectively. In contrast, cardiac myocytes incubated with CBHA for 6h and 24h elicited differential expression of 768 and 999 genes, respectively. We analyzed CBHA- and TSA-induced differentially expressed genes by Ingenuity Pathway (IPA), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Core_TF programs and discovered that CBHA and TSA impinged on several common gene networks. Thus, both HDACIs induced a repertoire of signaling kinases (PTEN-PI3K-AKT and MAPK) and transcription factors (Myc, p53, NFkB and HNF4A) representing canonical TGFβ, TNF-α, IFNγ and IL-6 specific networks. An overrepresentation of E2F, AP2, EGR1 and SP1 specific motifs was also found in the promoters of the differentially expressed genes. Apparently, TSA elicited predominantly TGFβ- and TNF-α-intensive gene networks regardless of the duration of treatment. In contrast, CBHA elicited TNF-α and IFNγ specific networks at 6 h, followed by elicitation of IL-6 and IFNγ-centered gene networks at 24h. Conclusions Our data show that both CBHA and TSA induced similar, but not identical, time-dependent, gene networks in H9c2 cardiac myocytes. Initially, both HDACIs impinged on numerous genes associated with adipokine signaling, intracellular metabolism and energetics, and cell cycle. A continued exposure to either CBHA or TSA led to the emergence of a number of apoptosis- and inflammation-specific gene networks that were apparently suppressed by both HDACIs. Based on these data we posit that the anti-inflammatory and anti-proliferative actions of HDACIs are myocyte-intrinsic. These findings advance our understanding of the mechanisms of actions of HDACIs on cardiac myocytes and reveal potential signaling pathways that may be targeted therapeutically.
    BMC Genomics 12/2012; 13(1):709. DOI:10.1186/1471-2164-13-709 · 3.99 Impact Factor
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    • "It is worth noting that myomiRs are naturally able to specify and maintain the muscle identity of a tissue because forced expression of miR-1 in epithelioid HeLa cells or in embryonic stem cells represses non-muscle genes, while inducing an expression profile reminiscent of muscle cells [54,55]. The transcription factor Serum Response Factor (SRF) and myogenic regulatory factors (MRFs) such as Myocyte Enhancer Factor 2 (MEF2), MyoD and myogenin [56] regulate myomiR expression during muscle tissue differentiation by binding specific promoter and/or enhancer sites on target miRNAs genes. "
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    ABSTRACT: There is growing evidence that interconnections among molecular pathways governing tissue differentiation are nodal points for malignant transformation. In this scenario, microRNAs appear as crucial players. This class of non-coding small regulatory RNA molecules controls developmental programs by modulating gene expression through post-transcriptional silencing of target mRNAs. During myogenesis, muscle-specific and ubiquitously-expressed microRNAs tightly control muscle tissue differentiation. In recent years, microRNAs have emerged as prominent players in cancer as well. Rhabdomyosarcoma is a pediatric skeletal muscle-derived soft-tissue sarcoma that originates from myogenic precursors arrested at different stages of differentiation and that continue to proliferate indefinitely. MicroRNAs involved in muscle cell fate determination appear down-regulated in rhabdomyosarcoma primary tumors and cell lines compared to their normal counterparts. More importantly, they behave as tumor suppressors in this malignancy, as their re-expression is sufficient to restore the differentiation capability of tumor cells and to prevent tumor growth in vivo. In addition, up-regulation of pro-oncogenic microRNAs has also been recently detected in rhabdomyosarcoma. In this review, we provide an overview of current knowledge on microRNAs de-regulation in rhabdomyosarcoma. Additionally, we examine the potential of microRNAs as prognostic and diagnostic markers in this soft-tissue sarcoma, and discuss possible therapeutic applications and challenges of a "microRNA therapy".
    Molecular Cancer 09/2011; 10(1):120. DOI:10.1186/1476-4598-10-120 · 4.26 Impact Factor
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    • "In addition, there is increasing evidence for the involvement of microRNAs in myopathies [14-16]. A number of microRNAs, including muscle-specific and non-muscle-specific miRNAs, have been characterized as regulators of skeletal muscle development and diseases [17-20] as well as of skeletal muscle remodeling [21]. Three muscle-specific miRNAs (miR-1, miR-133, and miR-206), with multiple key roles in the control of muscle growth and differentiation, have been the focus of intense research. "
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    ABSTRACT: To compare the microRNA (miRNA) expression profiles in neurons and innervated muscles after sciatic nerve entrapment using a non-constrictive silastic tube, subsequent surgical decompression, and denervation injury. The experimental L4-L6 spinal segments, dorsal root ganglia (DRGs), and soleus muscles from each experimental group (sham control, denervation, entrapment, and decompression) were analyzed using an Agilent rat miRNA array to detect dysregulated miRNAs. In addition, muscle-specific miRNAs (miR-1, -133a, and -206) and selectively upregulated miRNAs were subsequently quantified using real-time reverse transcription-polymerase chain reaction (real-time RT-PCR). In the soleus muscles, 37 of the 47 miRNAs (13.4% of the 350 unique miRNAs tested) that were significantly downregulated after 6 months of entrapment neuropathy were also among the 40 miRNAs (11.4% of the 350 unique miRNAs tested) that were downregulated after 3 months of decompression. No miRNA was upregulated in both groups. In contrast, only 3 miRNAs were upregulated and 3 miRNAs were downregulated in the denervated muscle after 6 months. In the DRGs, 6 miRNAs in the entrapment group (miR-9, miR-320, miR-324-3p, miR-672, miR-466b, and miR-144) and 3 miRNAs in the decompression group (miR-9, miR-320, and miR-324-3p) were significantly downregulated. No miRNA was upregulated in both groups. We detected 1 downregulated miRNA (miR-144) and 1 upregulated miRNA (miR-21) after sciatic nerve denervation. We were able to separate the muscle or DRG samples into denervation or entrapment neuropathy by performing unsupervised hierarchal clustering analysis. Regarding the muscle-specific miRNAs, real-time RT-PCR analysis revealed an approximately 50% decrease in miR-1 and miR-133a expression levels at 3 and 6 months after entrapment, whereas miR-1 and miR-133a levels were unchanged and were decreased after decompression at 1 and 3 months. In contrast, there were no statistical differences in the expression of miR-206 during nerve entrapment and after decompression. The expression of muscle-specific miRNAs in entrapment neuropathy is different from our previous observations in sciatic nerve denervation injury. This study revealed the different involvement of miRNAs in neurons and innervated muscles after entrapment neuropathy and denervation injury, and implied that epigenetic regulation is different in these two conditions.
    BMC Musculoskeletal Disorders 08/2010; 11(1):181. DOI:10.1186/1471-2474-11-181 · 1.72 Impact Factor
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