Transcriptome and Proteome Exploration to Model Translation Efficiency and Protein Stability in Lactococcus lactis

Abstract

This genome-scale study analysed the various parameters influencing protein levels in cells. To achieve this goal, the model bacterium Lactococcus lactis was grown at steady state in continuous cultures at different growth rates, and proteomic and transcriptomic data were thoroughly compared. Ratios of mRNA to protein were highly variable among proteins but also, for a given gene, between the different growth conditions. The modeling of cellular processes combined with a data fitting modeling approach allowed both translation efficiencies and degradation rates to be estimated for each protein in each growth condition. Estimated translational efficiencies and degradation rates strongly differed between proteins and were tested for their biological significance through statistical correlations with relevant parameters such as codon or amino acid bias. These efficiencies and degradation rates were not constant in all growth conditions and were inversely proportional to the growth rate, indicating a more efficient translation at low growth rate but an antagonistic higher rate of protein degradation. Estimated protein median half-lives ranged from 23 to 224 min, underlying the importance of protein degradation notably at low growth rates. The regulation of intracellular protein level was analysed through regulatory coefficient calculations, revealing a complex control depending on protein and growth conditions. The modeling approach enabled translational efficiencies and protein degradation rates to be estimated, two biological parameters extremely difficult to determine experimentally and generally lacking in bacteria. This method is generic and can now be extended to other environments and/or other micro-organisms.

Author Summary

This work is in the field of systems biology. Via an in-depth comparison of proteomic and transcriptomic data in various culture conditions, our objective was to better understand the regulation of protein levels. We have demonstrated that bacteria exert a tight control on intracellular protein levels, through a multi-level regulation involving translation but also dilution due to growth and protein degradation. We have estimated translational efficiencies and protein degradation rates by modeling. These two biological parameters are extremely difficult to measure experimentally and have not been previously determined in bacteria. We have found that they are growth rate dependent, indicating a fine control of translation and degradation processes. We have worked with the small genome bacterium Lactococcus lactis on a limited number of mRNA-protein couples but keeping in mind that this approach could be extended to other micro-organisms and biological phenomena. We have exhibited that mathematical modeling associated to experimental steady-states cultures is a powerful tool to understand microbial physiology.