Tobias Maier

The correlation between mRNA and protein abundances in the cell has been reported to be notoriously poor. Recent technological advances in the quantitative analysis of mRNA and protein species in complex samples allow the detailed analysis of this pathway at the center of biological systems. We give an overview of available methods for the identification and quantification of free and ribosome-bound mRNA, protein abundances and individual protein turnover rates. We review available literature on the correlation of mRNA and protein abundances and discuss biological and technical parameters influencing the correlation of these central biological molecules.

Simply Mycoplasma The bacterium Mycoplasma pneumoniae , a human pathogen, has a genome of reduced size and is one of the simplest organisms that can reproduce outside of host cells. As such, it represents an excellent model organism in which to attempt a systems-level understanding of its biological organization. Now three papers provide a comprehensive and quantitative analysis of the proteome, the metabolic network, and the transcriptome of M. pneumoniae (see the Perspective by Ochman and Raghavan ). Anticipating what might be possible in the future for more complex organisms, Kühner et al. (p. 1235 ) combine analysis of protein interactions by mass spectrometry with extensive structural information on M. pneumoniae proteins to reveal how proteins work together as molecular machines and map their organization within the cell by electron tomography. The manageable genome size of M. pneumoniae allowed Yus et al. (p. 1263 ) to map the metabolic network of the organism manually and validate it experimentally. Analysis of the network aided development of a minimal medium in which the bacterium could be cultured. Finally, G‡ell et al. (p. 1268 ) applied state-of-the-art sequencing techniques to reveal that this “simple” organism makes extensive use of noncoding RNAs and has exon- and intron-like structure within transcriptional operons that allows complex gene regulation resembling that of eukaryotes.

Simply Mycoplasma The bacterium Mycoplasma pneumoniae , a human pathogen, has a genome of reduced size and is one of the simplest organisms that can reproduce outside of host cells. As such, it represents an excellent model organism in which to attempt a systems-level understanding of its biological organization. Now three papers provide a comprehensive and quantitative analysis of the proteome, the metabolic network, and the transcriptome of M. pneumoniae (see the Perspective by Ochman and Raghavan ). Anticipating what might be possible in the future for more complex organisms, Kühner et al. (p. 1235 ) combine analysis of protein interactions by mass spectrometry with extensive structural information on M. pneumoniae proteins to reveal how proteins work together as molecular machines and map their organization within the cell by electron tomography. The manageable genome size of M. pneumoniae allowed Yus et al. (p. 1263 ) to map the metabolic network of the organism manually and validate it experimentally. Analysis of the network aided development of a minimal medium in which the bacterium could be cultured. Finally, G‡ell et al. (p. 1268 ) applied state-of-the-art sequencing techniques to reveal that this “simple” organism makes extensive use of noncoding RNAs and has exon- and intron-like structure within transcriptional operons that allows complex gene regulation resembling that of eukaryotes.

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.