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      Mapping the human skeletal muscle proteome: progress and potential

      1 , 1 , 1
      Expert Review of Proteomics
      Informa UK Limited

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          Muscles, exercise and obesity: skeletal muscle as a secretory organ.

          During the past decade, skeletal muscle has been identified as a secretory organ. Accordingly, we have suggested that cytokines and other peptides that are produced, expressed and released by muscle fibres and exert either autocrine, paracrine or endocrine effects should be classified as myokines. The finding that the muscle secretome consists of several hundred secreted peptides provides a conceptual basis and a whole new paradigm for understanding how muscles communicate with other organs, such as adipose tissue, liver, pancreas, bones and brain. However, some myokines exert their effects within the muscle itself. Thus, myostatin, LIF, IL-6 and IL-7 are involved in muscle hypertrophy and myogenesis, whereas BDNF and IL-6 are involved in AMPK-mediated fat oxidation. IL-6 also appears to have systemic effects on the liver, adipose tissue and the immune system, and mediates crosstalk between intestinal L cells and pancreatic islets. Other myokines include the osteogenic factors IGF-1 and FGF-2; FSTL-1, which improves the endothelial function of the vascular system; and the PGC-1α-dependent myokine irisin, which drives brown-fat-like development. Studies in the past few years suggest the existence of yet unidentified factors, secreted from muscle cells, which may influence cancer cell growth and pancreas function. Many proteins produced by skeletal muscle are dependent upon contraction; therefore, physical inactivity probably leads to an altered myokine response, which could provide a potential mechanism for the association between sedentary behaviour and many chronic diseases.
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            Current two-dimensional electrophoresis technology for proteomics.

            Two-dimensional gel electrophoresis (2-DE) with immobilized pH gradients (IPGs) combined with protein identification by mass spectrometry (MS) is currently the workhorse for proteomics. In spite of promising alternative or complementary technologies (e.g. multidimensional protein identification technology, stable isotope labelling, protein or antibody arrays) that have emerged recently, 2-DE is currently the only technique that can be routinely applied for parallel quantitative expression profiling of large sets of complex protein mixtures such as whole cell lysates. 2-DE enables the separation of complex mixtures of proteins according to isoelectric point (pI), molecular mass (Mr), solubility, and relative abundance. Furthermore, it delivers a map of intact proteins, which reflects changes in protein expression level, isoforms or post-translational modifications. This is in contrast to liquid chromatography-tandem mass spectrometry based methods, which perform analysis on peptides, where Mr and pI information is lost, and where stable isotope labelling is required for quantitative analysis. Today's 2-DE technology with IPGs (Görg et al., Electrophoresis 2000, 21, 1037-1053), has overcome the former limitations of carrier ampholyte based 2-DE (O'Farrell, J. Biol. Chem. 1975, 250, 4007-4021) with respect to reproducibility, handling, resolution, and separation of very acidic and/or basic proteins. The development of IPGs between pH 2.5-12 has enabled the analysis of very alkaline proteins and the construction of the corresponding databases. Narrow-overlapping IPGs provide increased resolution (delta pI = 0.001) and, in combination with prefractionation methods, the detection of low abundance proteins. Depending on the gel size and pH gradient used, 2-DE can resolve more than 5000 proteins simultaneously (approximately 2000 proteins routinely), and detect and quantify < 1 ng of protein per spot. In this article we describe the current 2-DE/MS workflow including the following topics: sample preparation, protein solubilization, and prefractionation; protein separation by 2-DE with IPGs; protein detection and quantitation; computer assisted analysis of 2-DE patterns; protein identification and characterization by MS; two-dimensional protein databases.
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              Mitochondrial fission and remodelling contributes to muscle atrophy.

              Mitochondria are crucial organelles in the production of energy and in the control of signalling cascades. A machinery of pro-fusion and fission proteins regulates their morphology and subcellular localization. In muscle this results in an orderly pattern of intermyofibrillar and subsarcolemmal mitochondria. Muscular atrophy is a genetically controlled process involving the activation of the autophagy-lysosome and the ubiquitin-proteasome systems. Whether and how the mitochondria are involved in muscular atrophy is unknown. Here, we show that the mitochondria are removed through autophagy system and that changes in mitochondrial network occur in atrophying muscles. Expression of the fission machinery is per se sufficient to cause muscle wasting in adult animals, by triggering organelle dysfunction and AMPK activation. Conversely, inhibition of the mitochondrial fission inhibits muscle loss during fasting and after FoxO3 overexpression. Mitochondrial-dependent muscle atrophy requires AMPK activation as inhibition of AMPK restores muscle size in myofibres with altered mitochondria. Thus, disruption of the mitochondrial network is an essential amplificatory loop of the muscular atrophy programme.
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                Author and article information

                Journal
                Expert Review of Proteomics
                Expert Review of Proteomics
                Informa UK Limited
                1478-9450
                1744-8387
                August 14 2017
                September 02 2017
                August 14 2017
                September 02 2017
                : 14
                : 9
                : 825-839
                Affiliations
                [1 ] Department of Biomedical Sciences for Health, University of Milan, Segrate, Milan, Italy
                Article
                10.1080/14789450.2017.1364996
                28780899
                d0fd4a29-f938-4b51-875c-b77cdfa5fa83
                © 2017
                History

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