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Delayed denervation-induced muscle atrophy in Opg knockout mice

ABSTRACT: Recent evidence has shown a crucial role for the osteoprotegerin/receptor activator of nuclear factor κ-B ligand/RANK (OPG/RANKL/RANK) signaling axis not only in bone but also in muscle tissue; however, there is still a lack of understanding of its effects on muscle atrophy. Here, we found that denervated Opg knockout mice displayed better functional recovery and delayed muscle atrophy, especially in a specific type IIB fiber. Moreover, OPG deficiency promoted milder activation of the ubiquitin-proteasome pathway, which further verified the protective role of Opg knockout in denervated muscle damage. Furthermore, transcriptome sequencing indicated that Opg knockout upregulated the expression of Inpp5k, Rbm3, and Tet2 and downregulated that of Deptor in denervated muscle. In vitro experiments revealed that satellite cells derived from Opg knockout mice displayed a better differentiation ability than those acquired from wild-type littermates. Higher expression levels of Tet2 were also observed in satellite cells derived from Opg knockout mice, which provided a mechanistic basis for the protective effects of Opg knockout on muscle atrophy. Taken together, our findings uncover the novel role of Opg in muscle atrophy process and extend the current understanding in the OPG/RANKL/RANK signaling axis.

ORGANISM(S): Mus musculus

PROVIDER: GSE220152 | GEO | 2023/05/01

REPOSITORIES: GEO

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Project description:In skeletal muscle, the pattern of electrical activity regulates the expression of proteins involved in synaptic transmission, contraction and metabolism. Disruptions in electrical activity, resulting from prolonged bed-rest, cast-immobilization or trauma, inevitably lead to muscle atrophy. The mechanisms that regulate muscle atrophy are poorly understood, but it seems likely that changes in gene expression play a key role in initiating and maintaining a muscle atrophy program. Previously, we found that Runx1, a transcription factor previously termed AML1, was substantially induced in muscle following denervation. More recently, we sought to determine whether this increase in Runx1 expression may be causally related to the morphological changes in skeletal muscle that accompany muscle disuse, notably muscle atrophy. We found that Runx1 is indeed required to sustain muscle and to minimize atrophy following denervation. Experiments described here are designed to identify the genes that are regulated by Runx1 in skeletal muscle with the particular goal of identifying genes that regulate muscle atrophy. We propose to use microarray analysis to identify genes, expressed in skeletal muscle, that are mis-regulated in mice lacking Runx1. We inactivated runx1 selectively in skeletal muscle and found that denervated myofibers in mutant mice atrophy far more (90% atrophy) than in wild-type mice (30% atrophy). We therefore reason that Runx1 activates and/or represses genes that are required to sustain muscle and to minimize atrophy. We generated MCK::cre; runx1f/- and runx1f/- control mice. In normal mice, an increase in runx1 expression is detected by two days after denervation and is maximal by five days after denervation. Muscle atrophy is first evident between one and two weeks after denervation. As we wish to avoid detecting global changes in gene expression that are associated with late stages of muscle atrophy, we plan to denervate muscle for three or five days and to compare gene expression in dissected innervated and denervated muscles from mutant and control mice. We will generate thirty samples for comparison-5 replicates per condition: Samples 1-3 from runx1f/- control mice. (1) innervated tibialis anterior muscles (TA); (2) 3-day-denervated TA; (3) 5-day-denervated TA. Samples 4-6 from MCK::cre; runx1f/- mice. (4) innervated TA; (5) 3-day-denervated TA; (6) 5-day-denervated TA. We obtain sufficient total RNA (10 micrograms) from each dissected muscle to avoid pooling samples. We will analyze adult mice of the same age (~six weeks after birth; most will be littermates) and sex-male. It is difficult to anticipate how many genes will be identified in this screen, as few target genes for Runx1 have been identified in any cell type and none in skeletal muscle. Moreover, although we would prefer to focus our attention on genes that are strongly dependent upon Runx1 expression (e.g. more than 5-fold difference in expression in wild-type and mutant mice), we do not know the extent to which target gene expression will depend upon Runx1. For these reasons, in these experiments, we will analyze expression from five âidenticalâ samples, so that we can be confident that even small (e.g. three-fold) differences in expression can be reliably determined. Importantly, in order to confirm results obtained from the microarray data, we will use other assays (RNase protection) to measure RNA expression of candidate genes in innervated and denervated muscles of wild-type and mutant mice.

Project description:Background This work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection (mostly Staphylococcus aureus). The infection alters the RANK/RANKL/OPG signalling dynamics that regulates osteoblasts and osteoclasts behaviour in bone remodelling, i.e. the resorption and mineralization activity. The infection rapidly leads to severe bone loss, necrosis of the affected portion, and it may even spread to other parts of the body. On the other hand, osteoporosis is not a bacterial infection but similarly is a defective bone pathology arising due to imbalances in the RANK/RANKL/OPG molecular pathway, and due to the progressive weakening of bone structure. Results Since both osteoporosis and osteomyelitis cause loss of bone mass, we focused on comparing the dynamics of these diseases by means of computational models. Firstly, we performed meta-analysis on a gene expression data of normal, osteoporotic and osteomyelitis bone conditions. We mainly focused on RANKL/OPG signalling, the TNF and TNF receptor superfamilies and the NF-kB pathway. Using information from the gene expression data we estimated parameters for a novel model of osteoporosis and of osteomyelitis. Our models could be seen as a hybrid ODE and probabilistic verification modelling framework which aims at investigating the dynamics of the effects of the infection in bone remodelling. Finally we discuss different diagnostic estimators defined by formal verification techniques, in order to assess different bone pathologies (osteopenia, osteoporosis and osteomyelitis) in an effective way. Conclusions We present a modeling framework able to reproduce aspects of the different bone remodeling defective dynamics of osteomyelitis and osteoporosis. We report that the verification-based estimators are meaningful in the light of a feed forward between computational medicine and clinical bioinformatics Model is encoded by Ruby and submitted and curated to BioModels by Ahmad Zyoud

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Delayed denervation-induced muscle atrophy in Opg knockout mice

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