label-free lc-ms profiling of skeletal muscle reveals heart-type fatty acid binding protein as a candidate biomarker of aerobic capacity

label-free lc-ms profiling of skeletal muscle reveals heart-type fatty acid binding protein as a candidate biomarker of aerobic capacity

;Zulezwan A. Malik;James N. Cobley;James P. Morton;Graeme L. Close;Ben J. Edwards;Lauren G. Koch;Steven L. Britton;Jatin G. Burniston
north carolina medical journal 2013 Vol. 1 pp. 290-308
182
malik2013proteomeslabel-free

Abstract

Two-dimensional gel electrophoresis provides robust comparative analysis of skeletal muscle, but this technique is laborious and limited by its inability to resolve all proteins. In contrast, orthogonal separation by SDS-PAGE and reverse-phase liquid chromatography (RPLC) coupled to mass spectrometry (MS) affords deep mining of the muscle proteome, but differential analysis between samples is challenging due to the greater level of fractionation and the complexities of quantifying proteins based on the abundances of their tryptic peptides. Here we report simple, semi-automated and time efficient (i.e., 3 h per sample) proteome profiling of skeletal muscle by 1-dimensional RPLC electrospray ionisation tandem MS. Solei were analysed from rats (n = 5, in each group) bred as either high- or low-capacity runners (HCR and LCR, respectively) that exhibited a 6.4-fold difference (1,625 ± 112 m vs. 252 ± 43 m, p < 0.0001) in running capacity during a standardized treadmill test. Soluble muscle proteins were extracted, digested with trypsin and individual biological replicates (50 ng of tryptic peptides) subjected to LC-MS profiling. Proteins were identified by triplicate LC-MS/MS analysis of a pooled sample of each biological replicate. Differential expression profiling was performed on relative abundances (RA) of parent ions, which spanned three orders of magnitude. In total, 207 proteins were analysed, which encompassed almost all enzymes of the major metabolic pathways in skeletal muscle. The most abundant protein detected was type I myosin heavy chain (RA = 5,843 ± 897) and the least abundant protein detected was heat shock 70 kDa protein (RA = 2 ± 0.5). Sixteen proteins were significantly (p < 0.05) more abundant in HCR muscle and hierarchal clustering of the profiling data highlighted two protein subgroups, which encompassed proteins associated with either the respiratory chain or fatty acid oxidation. Heart-type fatty acid binding protein (FABPH) was 1.54-fold (p = 0.0064) more abundant in HCR than LCR soleus. This discovery was verified using selective reaction monitoring (SRM) of the y5 ion (551.21 m/z) of the doubly-charged peptide SLGVGFATR (454.19 m/z) of residues 23–31 of FABPH. SRM was conducted on technical replicates of each biological sample and exhibited a coefficient of variation of 20%. The abundance of FABPH measured by SRM was 2.84-fold greater (p = 0.0095) in HCR muscle. In addition, SRM of FABPH was performed in vastus lateralis samples of young and elderly humans with different habitual activity levels (collected during a previous study) finding FABPH abundance was 2.23-fold greater (p = 0.0396) in endurance-trained individuals regardless of differences in age. In summary, our findings in HCR/LCR rats provide protein-level confirmation for earlier transcriptome profiling work and show LC-MS is a viable means of profiling the abundance of almost all major metabolic enzymes of skeletal muscle in a highly parallel manner. Moreover, our approach is relatively more time efficient than techniques relying on orthogonal separations, and we demonstrate LC-MS profiling of the HCR/LCR selection model was able to highlight biomarkers that also exhibit differences in trained and untrained human muscle.

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154272
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10.3390/proteomes1030290
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