Determination of the average cellular copy number of 400 proteins under different growth conditions and integration with protein turnover and absolute mRNA levels reveals the dynamics of protein expression in the genome-reduced bacterium Mycoplasma pneumoniae.
Our study provides a fine-grained, quantitative picture to unprecedented detail in an established model organism for systems-wide studies.Our integrative approach reveals a novel, dynamic view on the processes, interactions and regulations underlying the central dogma pathway and the composition of protein complexes.Simulations using our quantitative data on mRNA, protein and turnover show how an organism copes with stochastic noise in gene expression in vivo.Our data serve as an important resource for colleagues both within our field of research and in related disciplines.
A hallmark of Systems Biology is the integration of diverse, large quantitative data sets with the aim to gain novel insights into how biological processes work. We measured individual mRNA and protein abundances as well as protein turnover in the bacterium Mycoplasma pneumoniae. This human pathogen is an ideal model organism for organism-wide studies. It can be readily cultured under laboratory conditions and it has a very small genome with only 690 protein-coding genes. This comparably low complexity allows for the exhaustive analysis of major cellular biomolecules avoiding constrains introduced by limitations of available analysis techniques.
Using a recently developed mass spectrometry-based approach, we determined the average cellular copy number for over 400 individual proteins under different growth and stress conditions. The 20 most abundant proteins, including Elongation factor Tu, cellular chaperones, and proteins involved in metabolizing glucose, the major energy source of M. pneumoniae account for nearly 44% of the total cellular protein mass. We observed abundance changes of many expected and several unexpected proteins in response to cellular stress, such as heat shock, DNA damage and osmotic stress, as well as along batch culture growth over 4 days.
Integration of the protein abundance data with quantitative mRNA measurements revealed a modest correlation between these two classes of biomolecules. However, for several classical stress-induced proteins, we observed a correlated induction of mRNA and protein in response to heat shock. A focused analysis of mRNA–protein abundance dynamics during batch culture growth suggested that the regulation of gene expression is largely decoupled from protein dynamics in M. pneumoniae, indicating extensive post-transcriptional and post-translational regulation influencing the cellular mRNA–protein ratios.
To investigate the factors influencing the cellular protein abundance, we measured individual protein turnover rates by mass spectrometry using a label-chase approach involving stable isotope-labelled amino acids. The average half-life of a protein in M. pneumoniae is 23 h. Based on the measured quantitative mRNA data, the protein abundances and their half-lives, we established an ordinary differential equations model for the estimation of individual in vivo protein degradation and translation efficiency rates. We found out that translation efficiency rather than protein turnover is the dominating factor influencing protein abundance. Using our abundance and turnover data, we additionally performed stochastic simulations of gene expression. We observed that long protein half-life and low translational efficiency buffers gene expression noise propagating from low cellular mRNA levels in vivo.
We compared the abundance ratios of proteins associating into complexes in vivo with their expected functional stoichiometries. We observed that for stable protein complexes, such as the GroEL/ES chaperonin or DNA gyrase, our measured abundance ratios reflected the expected subunit stoichiometries. More dynamic protein complexes, such as the DnaK/J/GrpE chaperone system or RNA polymerase, showed several unusual subunit ratios, pointing towards transient interaction of sub-stoichiometric subunits for function. A detailed, quantitative analysis of the ribosome, the largest cellular protein complex, revealed large abundance differences of the 51 subunits. This observation indicates a multi-functionality for several, abundant ribosomal proteins.
Finally, a comparison of the determined average cellular protein abundances with a different pathogenic bacterium, Leptospira interrogans, revealed that cellular protein abundances closely reflect their respective lifestyles.
Our study represents an organism-wide, quantitative analysis of cellular protein abundances. Integrating our proteomics data with determined mRNA levels and protein turnover rates reveals insights into the dynamic interplay and regulation of mRNA and proteins, the central biomolecules of a cell.
Biological function and cellular responses to environmental perturbations are regulated by a complex interplay of DNA, RNA, proteins and metabolites inside cells. To understand these central processes in living systems at the molecular level, we integrated experimentally determined abundance data for mRNA, proteins, as well as individual protein half-lives from the genome-reduced bacterium Mycoplasma pneumoniae. We provide a fine-grained, quantitative analysis of basic intracellular processes under various external conditions. Proteome composition changes in response to cellular perturbations reveal specific stress response strategies. The regulation of gene expression is largely decoupled from protein dynamics and translation efficiency has a higher regulatory impact on protein abundance than protein turnover. Stochastic simulations using in vivo data show how low translation efficiency and long protein half-lives effectively reduce biological noise in gene expression. Protein abundances are regulated in functional units, such as complexes or pathways, and reflect cellular lifestyles. Our study provides a detailed integrative analysis of average cellular protein abundances and the dynamic interplay of mRNA and proteins, the central biomolecules of a cell.