Abstract

Protein responses to extracellular cues are governed by gene transcription, mRNA degradation and translation, and protein degradation. In order to understand how these time-dependent processes cooperate to generate dynamic responses, we analyzed the response of human mammary cells to the epidermal growth factor (EGF). Integrating time-dependent transcript and protein data into a mathematical model, we inferred for several proteins their pre-and post-stimulus translation and degradation coefficients and found that they exhibit complex, time-dependent variation. Specifically, we identified strategies of protein production and degradation acting in concert to generate rapid, transient protein bursts in response to EGF. Remarkably, for some proteins, for which the response necessitates rapidly decreased abundance, cells exhibit a transient increase in the corresponding degradation coefficient. Our model and analysis allow inference of the kinetics of mRNA translation and protein degradation, without perturbing cells, and open a way to understanding the fundamental processes governing time-dependent protein abundance profiles.

Highlights

  • Protein abundance in eukaryotes is determined by a cascade of fundamental processes, which include transcription of DNA into pre-mRNA processed into mature mRNA molecules transported to the cytoplasm, where they may undergo decay or translation into proteins, which are eventually degraded

  • Protein responses to extracellular cues are governed by gene transcription, mRNA degradation and translation, and protein degradation

  • In order to understand how these time-dependent processes cooperate to generate dynamic responses, we analyzed the response of human mammary cells to the epidermal growth factor (EGF)

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Summary

Introduction

Protein abundance in eukaryotes is determined by a cascade of fundamental processes, which include transcription of DNA into pre-mRNA processed into mature mRNA molecules transported to the cytoplasm, where they may undergo decay or translation into proteins, which are eventually degraded. Correspondence between transcript abundance and the respective protein levels has been the subject of recent studies that performed concurrent systematic analyses of largescale mRNA and protein data under steady state in bacteria, yeast, and mammalian cells. Several studies found that the variation of protein levels can largely be explained by varying transcript abundance (Li et al, 2014; Lu et al, 2007), whereas a few investigations reported only limited correlation between mRNA and protein levels (Lundberg et al, 2010; Schwanhausser et al, 2011), calling for additional modes of regulation to explain changes in protein abundance (Lee et al, 2011; Maier et al, 2011; Vogel et al, 2010). The relative importance of the factors governing and controlling protein levels at steady state requires additional research, leave alone the significantly more complex alterations taking place in the course of a dynamic process

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