On Ribosome Load, Codon Bias and Protein Abundance

Different codons encoding the same amino acid are not used equally in protein-coding sequences. In bacteria, there is a bias towards codons with high translation rates. This bias is most pronounced in highly expressed proteins, but a recent study of synthetic GFP-coding sequences did not find a correlation between codon usage and GFP expression, suggesting that such correlation in natural sequences is not a simple property of translational mechanisms. Here, we investigate the effect of evolutionary forces on codon usage. The relation between codon bias and protein abundance is quantitatively analyzed based on the hypothesis that codon bias evolved to ensure the efficient usage of ribosomes, a precious commodity for fast growing cells. An explicit fitness landscape is formulated based on bacterial growth laws to relate protein abundance and ribosomal load. The model leads to a quantitative relation between codon bias and protein abundance, which accounts for a substantial part of the observed bias for E. coli. Moreover, by providing an evolutionary link, the ribosome load model resolves the apparent conflict between the observed relation of protein abundance and codon bias in natural sequences and the lack of such dependence in a synthetic gfp library. Finally, we show that the relation between codon usage and protein abundance can be used to predict protein abundance from genomic sequence data alone without adjustable parameters.

On Ribosome Load, Codon Bias and Protein Abundance

Different codons encoding the same amino acid are not used equally in protein-coding sequences. In bacteria, there is a bias towards codons with high translation rates. This bias is most pronounced in highly expressed proteins, but a recent study of synthetic GFP-coding sequences did not find a correlation between codon usage and GFP expression, suggesting that such correlation in natural sequences is not a simple property of translational mechanisms. Here, we investigate the effect of evolutionary forces on codon usage. The relation between codon bias and protein abundance is quantitatively analyzed based on the hypothesis that codon bias evolved to ensure the efficient usage of ribosomes, a precious commodity for fast growing cells. An explicit fitness landscape is formulated based on bacterial growth laws to relate protein abundance and ribosomal load. The model leads to a quantitative relation between codon bias and protein abundance, which accounts for a substantial part of the observed bias for E. coli. Moreover, by providing an evolutionary link, the ribosome load model resolves the apparent conflict between the observed relation of protein abundance and codon bias in natural sequences and the lack of such dependence in a synthetic gfp library. Finally, we show that the relation between codon usage and protein abundance can be used to predict protein abundance from genomic sequence data alone without adjustable parameters.

Investigation Of Leucine And Glutamic Acid Properties From The Nanoscale To The Macroscale

Aerosols are known to have important effects on climate, the atmosphere, and human health. The extent of those effects is unknown and largely depend on the interaction of aerosols with water in the atmosphere. Ambient aerosols are complex mixtures of both inorganic and organic compounds. The cloud condensation nuclei (CCN) activities, hygroscopic behavior and particle morphology of a monocarboxylic amino acid (leucine) and a dicarboxylic amino acid (glutamic acid) were investigated. Activation diameters at various supersaturation conditions were experimentally determined and compared with Köhler theoretical values. The theory accounts for both surface tension and the limited solubility of organic compounds. It was discovered that glutamic acid aerosols readily took on water both when relative humidity was less than 100% and when the supersaturation condition was reached, while leucine did not show any water activation at those conditions. Moreover, the study also suggests that Köhler theory describes CCN activity of organic compounds well when only surface tension of the compound is taken into account and complete solubility is assumed. Single parameter ¿ was also computed using both CCN data and hygroscopic growth factor (GF). The results of ¿ range from 0.17 to 0.53 using CCN data and 0.09 to 0.2 using GFs. Finally, the study suggests that during the water-evaporation/particle-nucleation process, crystallization from solution droplets takes place at different locations: for glutamic acid at the particles¿ center and leucine at the particles¿ boundary.