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.

Dimorphism in Shell Shape and Strength in Two Species of Emydid Turtle

This study investigates the mechanical implications of shell shape differences between males and females of two North American turtle species: Chrysemys picta and Glyptemys insculpta. These species show patterns of sexual dimorphism that are common to many species of turtle. Females have wider and more highly domed shells, whereas males tend to have flatter, more streamlined shells. In addition, the males of many terrestrial species have concave plastra, most likely to accommodate the domed shells of the females while mating. The purpose of this study was to determine whether the known morphological differences in male and female turtle shells are also associated with differences in shell strength. Landmark coordinate data were collected from the shells of males and females of both species. These data were used to create digital models of each shell for finite-element (FE) analysis. FE models were generated by transforming a single base model of a turtle shell to match the shapes of each specimen examined in this study. All models were assigned the same material properties and restraints. Twelve load cases, each representing a predator’s bite at a different location on the carapace, were applied separately to the models. Subsequently, Von Mises stresses were extracted for each element of each model. Overall, the shells of females of both species exhibited significantly lower maximum and average stresses for a given load than those of their male counterparts. Male G. insculpta exhibited significant increases in stresses because of the concave shape of their plastra. We suggest that the mechanical implications of shell shape differences between males and females may have a large impact on many aspects of the biology of these turtle species.

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.