Literature DB >> 16880987

ICAT-MS-MS time course analysis of atrophying mouse skeletal muscle cytosolic subproteome.

Marco Toigo1, Samuel Donohoe, Gina Sperrazzo, Bradley Jarrold, Feng Wang, Richard Hinkle, Elizabeth Dolan, Robert J Isfort, Ruedi Aebersold.   

Abstract

Skeletal muscle atrophy is a process in which protein degradation exceeds protein synthesis, resulting in a decrease of the muscle's physiological cross-sectional area and mass, and is often a serious consequence of numerous health problems. We used the isotope-coded affinity tag (ICAT) labelling approach and MS-MS to protein profile cytosolic subcellular fractions from mouse tibialis anterior skeletal muscle undergoing 0, 4, 8, or 16 days of immobilisation-induced atrophy. For the validation of peptide and protein identifications statistical algorithms were applied to the sequence database search results in order to obtain consistent sensitivity/error rates for protein and peptide identifications at each immobilisation time point. In this study, we identified and quantified a large number of mouse skeletal muscle proteins. At a protein probability (P) of P> or = 0.9 (corresponding to a false positive error rate of less than 1%) 807 proteins were identified (231, 226, 217 for 4, 8, 16 days of immobilisation and 133 for the control sample, respectively), from which 51 displayed altered protein abundance with atrophy. Due to randomness of data acquisition, a full time course could be generated only for 62 proteins, most of which displayed unchanged protein abundance. In spite of this, useful information about dataset characteristics and underlying biological processes could be obtained through gene over-representation analysis. 20 gene categories-mainly but not exclusively encoded by the subset of overlapping proteins--were consistently found to be significantly (p < 0.05) over-represented in all 4 sub-datasets.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 16880987     DOI: 10.1039/b507839c

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  8 in total

Review 1.  New fundamental resistance exercise determinants of molecular and cellular muscle adaptations.

Authors:  Marco Toigo; Urs Boutellier
Journal:  Eur J Appl Physiol       Date:  2006-08       Impact factor: 3.078

2.  Proteomic profiling of skeletal muscle plasticity.

Authors:  Kay Ohlendieck
Journal:  Muscles Ligaments Tendons J       Date:  2012-04-01

3.  Differential profiling of breast cancer plasma proteome by isotope-coded affinity tagging method reveals biotinidase as a breast cancer biomarker.

Authors:  Un-Beom Kang; Younghee Ahn; Jong Won Lee; Yong-Hak Kim; Joon Kim; Myeong-Hee Yu; Dong-Young Noh; Cheolju Lee
Journal:  BMC Cancer       Date:  2010-03-26       Impact factor: 4.430

4.  Skeletal muscle proteomics: current approaches, technical challenges and emerging techniques.

Authors:  Kay Ohlendieck
Journal:  Skelet Muscle       Date:  2011-02-01       Impact factor: 4.912

5.  Simultaneous Pathoproteomic Evaluation of the Dystrophin-Glycoprotein Complex and Secondary Changes in the mdx-4cv Mouse Model of Duchenne Muscular Dystrophy.

Authors:  Sandra Murphy; Michael Henry; Paula Meleady; Margit Zweyer; Rustam R Mundegar; Dieter Swandulla; Kay Ohlendieck
Journal:  Biology (Basel)       Date:  2015-06-10

6.  Muscle wasting in patients with end-stage renal disease or early-stage lung cancer: common mechanisms at work.

Authors:  Julien Aniort; Alexandre Stella; Carole Philipponnet; Anais Poyet; Cécile Polge; Agnès Claustre; Lydie Combaret; Daniel Béchet; Didier Attaix; Stéphane Boisgard; Marc Filaire; Eugénio Rosset; Odile Burlet-Schiltz; Anne-Elisabeth Heng; Daniel Taillandier
Journal:  J Cachexia Sarcopenia Muscle       Date:  2019-01-29       Impact factor: 12.910

7.  Intricate effects of primary motor neuronopathy on contractile proteins and metabolic muscle enzymes as revealed by label-free mass spectrometry.

Authors:  Ashling Holland; Thomas Schmitt-John; Paul Dowling; Paula Meleady; Michael Henry; Martin Clynes; Kay Ohlendieck
Journal:  Biosci Rep       Date:  2014-07-01       Impact factor: 3.840

8.  Mass spectrometric identification of dystrophin, the protein product of the Duchenne muscular dystrophy gene, in distinct muscle surface membranes.

Authors:  Sandra Murphy; Kay Ohlendieck
Journal:  Int J Mol Med       Date:  2017-07-27       Impact factor: 4.101

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.