Oral Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

The degrading business: Measurement of proteome turnover in intact animals (#95)

Robert J Beynon 1 , Dean E Hammond 1 , Deborah M Simpson 1 , Mark Prescott 1 , John Waters 1 , Jane L Hurst 1 , Edward Lau 2
  1. Institute of Integrative Biology, University of Liverpool, Liverpool, Merseyside, United Kingdom
  2. Cardiovascular Institute, Stanford University, Stanford, CA, United States of America

A steady state proteome is changing rapidly, as proteins are synthesised and degraded at rates that balance each other. Changes in protein abundance are caused by an imbalance in these opposing processes. Thus, a full definition of the proteome must include an understanding of the rate at which any protein is replaced. In a steady state, this can only be attained by monitoring the behaviour of a tracer, and at the proteome level, this means stable isotope precursors. These can be simple (e.g. deuterated water or 15N NH4Cl) or more complex (stable isotope labelled amino acids). The labelling strategies, isotope incorporation patterns and treatment of the kinetic data vary with the labelling protocol. For systematic comparison of two labelling methods we have taken two cohorts of identical, inbred C57BL/6J mice and measured protein turnover rates in four tissues, using either [2H2]O (heavy water, ‘HW’, supplied in drinking water) or [13C6] lysine (amino acid, ‘AA’, provided as a supplement to normal laboratory chow). We have then compared the measurement of turnover using the two methods, asking ‘do we obtain the same values?’.

Tryptic digests were analysed by LC-MS/MS and data were processed using Crux, and label incorporation using open source software RIAna, (written by EL, see associated poster). The major difference between the two labelling protocols lies in the speed at which the precursor equilibrates within each tissue, and this delay can lead to distortion in the determination of the rate of turnover, particularly for high turnover proteins. However, the precursor pool labelling trajectory is measurable using GC-MS of plasma for HW, and analysis of di-lysine peptides for AA. Correction for precursor pool labelling leads to rate constants that are very similar between the two methods. Thus, either approach can yield proteome-wide turnover measurements with high accuracy and precision.