Investigating Muscle Protein Turnover on a Protein-by-Protein Basis Using Dynamic Proteome Profiling

Abstract

Proteomic investigations aim to achieve broad-scale characterisation of the protein complement of muscle and also perform non-targeted differential analysis of the muscle proteome under different conditions (e.g. health versus disease). In the majority, proteomic studies have generated new insight by linking patterns of protein abundance or post-translational modification with different functional states. Such information is regarded as being static because the measurements of abundance or post-translational state represent a ‘snapshot’ of the muscle proteome under certain conditions at a particular point in time. As such, these data do not include kinetic information and cannot be used to study dynamic aspects of the muscle proteome, including protein turnover or the relative contributions that synthesis and degradation make to changes in protein abundance. For instance, a series of samples collected over time can be used to build a picture of temporal changes in muscle protein abundance, but the question of how the time-dependent changes in the abundance of proteins occurred cannot be answered without also knowing whether (1) the change in a protein’s abundance was matched by a greater or lesser rate of synthesis of that protein, and/or (2) whether a change in degradation rate might also have contributed to the difference in protein abundance. Dynamic Proteome Profiling is a new technique that aims to address these questions by offering insight to the synthesis, abundance and degradation of individual proteins in the muscle of humans [1], as well as non-human laboratory animals and cell cultures. Dynamic Proteome Profiling is built on the culmination of a long history of research and methodological development in the fields of stable isotopic labelling, proteomics and computational biology. This chapter aims to highlight the contributions from these separate pillars of research and explain how they are brought together in order to perform Dynamic Proteome Profiling in humans.