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Label‐free profiling of skeletal muscle using high‐definition mass spectrometry
Authors:Jatin G. Burniston  Joanne Connolly  Heikki Kainulainen  Steven L. Britton  Lauren G. Koch
Affiliation:1. Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, , Liverpool, UK;2. Waters Inc, , Manchester, UK;3. Department of Biology of Physical Activity, University of Jyv?skyl?, , Jyv?skyl?, Finland;4. Department of Anesthesiology, University of Michigan, , Ann Arbor, MI, USA
Abstract:We report automated and time‐efficient (2 h per sample) profiling of muscle using ultra‐performance LC coupled directly with high‐definition MS (HDMSE). Soluble proteins extracted from rat gastrocnemius (n = 10) were digested with trypsin and analyzed in duplicate using a 90 min RPLC gradient. Protein identification and label‐free quantitation were performed from HDMSE spectra analyzed using Progenesis QI for Proteomics software. In total 1514 proteins were identified. Of these, 811 had at least three unique peptides and were subsequently used to assess the dynamic range and precision of LC‐HDMSE label‐free profiling. Proteins analyzed by LC‐HDMSE encompass the entire complement of glycolytic, β‐oxidation, and tricarboxylic acid enzymes. In addition, numerous components of the electron transport chain and protein kinases involved in skeletal muscle regulation were detected. The dynamic range of protein abundances spanned four orders of magnitude. The correlation between technical replicates of the ten biological samples was R2 = 0.9961 ± 0.0036 (95% CI = 0.9940 – 0.9992) and the technical CV averaged 7.3 ± 6.7% (95% CI = 6.87 – 7.79%). This represents the most sophisticated label‐free profiling of skeletal muscle to date.
Keywords:Animal proteomics  Data‐independent acquisition  Ion mobility  LC‐MS
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