Comparing Simplification Strategies for the Skeletal Muscle Proteome

Abstract

Skeletal muscle is a complex tissue that is dominated by the presence of a few abundant proteins. This wide dynamic range can mask the presence of lower abundance proteins, which can be a confounding factor in large-scale proteomic experiments. In this study, we have investigated a number of pre-fractionation methods, at both the protein and peptide level, for the characterization of the skeletal muscle proteome. The analyses revealed that the use of OFFGEL isoelectric focusing yielded the largest number of protein identifications (>750) compared to alternative gel-based and protein equalization strategies. Further, OFFGEL led to a substantial enrichment of a different sub-population of the proteome. Filter-aided sample preparation (FASP), coupled to peptide-level OFFGEL provided more confidence in the results due to a substantial increase in the number of peptides assigned to each protein. The findings presented here support the use of a multiplexed approach to proteome characterization of skeletal muscle, which has a recognized imbalance in the dynamic range of its protein complement.

Keywords: FASP; OFFGEL; ProteoMiner; protein equalization; proteome simplification; skeletal muscle.

Figure 1

A multiplexed approach to characterising the skeletal muscle proteome skeletal muscle from common carp was homogenized and subjected to a range of separation techniques prior to mass spectrometric analyses. The soluble protein fraction was either separated by 1-D SDS-PAGE or simplified by either ProteoMiner protein equalization or OFFGEL isoelectric focusing before the eluted fractions were analysed by 1-D SDS-PAGE. A further strategy analysed the whole protein homogenate by sampling directly in the peptide space. Proteins were digested in-solution prior to OFFGEL fractionation.

Figure 2

Protein identifications following sample pre-fractionation. The number of proteins identified following each fractionation protocol was determined. Data shown was determined from three biological replicates for each technique.

Figure 3

Gene ontology analysis. Gene ontology analysis was performed using the PANTHER software. Proteins were grouped according to (A) biological function, (B) molecular function and (C) cellular component. 1-D SDS-PAGE is represented by blue bars, ProteoMiner by red, OFFGEL by green and FASP by yellow.

Figure 3

Gene ontology analysis. Gene ontology analysis was performed using the PANTHER software. Proteins were grouped according to (A) biological function, (B) molecular function and (C) cellular component. 1-D SDS-PAGE is represented by blue bars, ProteoMiner by red, OFFGEL by green and FASP by yellow.

Figure 4

Overlap of Protein Identifications. There were 80 identified proteins common to all experimental approaches. OFFGEL analysis yielded the greatest number of uniquely identified proteins, followed by ProteoMiner, FASP with 1-D SDS-PAGE having the fewest.