Absolute Quantification of Protein and mRNA Abundances Demonstrate Variability in Gene-Specific Translation Efficiency in Yeast
Journal article, 2017

Protein synthesis is the most energy-consuming process in a proliferating cell, and understanding what controls protein abundances represents a key question in biology and biotechnology. We quantified absolute abundances of 5,354 mRNAs and 2,198 proteins in Saccharomyces cerevisiae under ten environmental conditions and protein turnover for 1,384 proteins under a reference condition. The overall correlation between mRNA and protein abundances across all conditions was low (0.46), but for differentially expressed proteins (n = 202), the median mRNA-protein correlation was 0.88. We used these data to model translation efficiencies and found that they vary more than 400-fold between genes. Non-linear regression analysis detected that mRNA abundance and translation elongation were the dominant factors controlling protein synthesis, explaining 61% and 15% of its variance. Metabolic flux balance analysis further showed that only mitochondrial fluxes were positively associated with changes at the transcript level. The present dataset represents a crucial expansion to the current resources for future studies on yeast physiology.

Growth-Rate

Metabolic Fluxes

Sequencing Technologies

Lactococcus-Lactis

Cell-Wall

In-Vivo

Dynamics

Transcriptional Control

Saccharomyces-Cerevisiae

Escherichia-Coli

Author

Petri-Jaan Lahtvee

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Benjamin José Sanchez Barja

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Agata Smialowska

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

S. Kasvandik

University of Tartu

Ibrahim El-Semman

Technical University of Denmark (DTU)

Francesco Gatto

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Jens B Nielsen

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Cell Systems

24054712 (ISSN) 24054720 (eISSN)

Vol. 4 5 495-504.e5

Subject Categories

Biological Sciences

DOI

10.1016/j.cels.2017.03.003

More information

Latest update

5/17/2018