A Proteomics Approach to Profiling the Temporal Translational Response to Stress and Growth

Daniel A Rothenberg,J Matthew Taliaferro,Sabrina M Huber,Thomas J Begley,Peter C Dedon,Forest M White

doi:10.1016/j.isci.2018.11.004

Abstract

SummaryTo quantify dynamic protein synthesis rates, we developed MITNCAT, a method combining multiplexed isobaric mass tagging with pulsed SILAC (pSILAC) and bio-orthogonal non-canonical amino acid tagging (BONCAT) to label newly synthesized proteins with azidohomoalanine (Aha), thus enabling high temporal resolution across multiple conditions in a single analysis. MITNCAT quantification of protein synthesis rates following induction of the unfolded protein response revealed global down-regulation of protein synthesis, with stronger down-regulation of glycolytic and protein synthesis machinery proteins, but up-regulation of several key chaperones. Waves of temporally distinct protein synthesis were observed in response to epidermal growth factor, with altered synthesis detectable in the first 15 min. Comparison of protein synthesis with mRNA sequencing and ribosome footprinting distinguished protein synthesis driven by increased transcription versus increased translational efficiency. Temporal delays between ribosome occupancy and protein synthesis were observed and found to correlate with altered codon usage in significantly delayed proteins.

Highlights

Cellular response to perturbation often leads to a change in cell state, accompanied by dynamic alterations in protein synthesis and degradation that result in changes in protein expression levels (GolanLavi et al, 2017)
With the goal of developing a method that would allow for high sensitivity analysis of newly translated proteins at multiple time points with high temporal resolution, we developed MITNCAT, combining bio-orthogonal non-canonical amino acid tagging (BONCAT) with pulsed SILAC (pSILAC) and using multiplexed isobaric tandem mass tagging (TMT) (Thompson et al, 2003) to quantitatively compare translation rates for thousands of proteins across ten different conditions in a single mass spectrometry (MS) experiment
Realizing that protein synthesis rates are likely dynamic, we developed MITNCAT, a method to accurately quantify the temporal dynamics of protein synthesis rates at a global scale

Summary

Introduction

Cellular response to perturbation often leads to a change in cell state, accompanied by dynamic alterations in protein synthesis and degradation that result in changes in protein expression levels (GolanLavi et al, 2017). Measuring changes in mRNA abundance is commonly used to estimate changes in protein expression; relative mRNA abundance has been shown to be an incomplete predictor of protein synthesis and abundance (Schwanhausser et al, 2011; Jovanovic et al, 2015) because translation is a highly regulated process that can be modulated by signaling pathways (Rowlands et al, 1988; Feng et al, 1992; Chen and London, 1995; Berlanga et al, 1999; Gingras et al, 2001; Novoa et al, 2003), RNA structural elements (Filbin and Kieft, 2009), and tRNA isoacceptor availability (Chan et al, 2010, 2012; Chionh et al, 2016). RFP analysis involves the isolation and sequencing of $30 nucleotide mRNA fragments shielded by the ribosome from nuclease degradation (Ingolia et al, 2009; Ingolia, 2016). RFP and TE provide a fairly accurate estimate of potential protein synthesis rates, these measurements do not account for stalled ribosomes and have been shown to be less representative of protein synthesis rates during cell stress response (Iwasaki and Ingolia, 2017; Liu et al, 2017)

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Conclusion