Optimality of codon usage in Escherichia coli due to load minimization

The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, an ability which in term is designated "load minimization". One parameter involved in calculating the load minimizing property of the genetic code is codon usage. In most bacteria, synonymous codons are not used with equal frequencies. Different factors have been proposed to contribute to codon usage preference. It has been shown that the codon preference is correlated with the composition of the tRNA pool. Selection for translational efficiency and translational accuracy both result in such a correlation. In this work, it is shown that codon usage bias in Escherichia coli works so as to minimize the consequences of translational errors, i.e. optimized for load minimization.     

The Selective Advantage of Synonymous Codon Usage Bias in Salmonella

The genetic code in mRNA is redundant, with 61 sense codons translated into 20 different amino acids. Individual amino acids are encoded by up to six different codons but within codon families some are used more frequently than others. This phenomenon is referred to as synonymous codon usage bias. The genomes of free-living unicellular organisms such as bacteria have an extreme codon usage bias and the degree of bias differs between genes within the same genome. The strong positive correlation between codon usage bias and gene expression levels in many microorganisms is attributed to selection for translational efficiency. However, this putative selective advantage has never been measured in bacteria and theoretical estimates vary widely. By systematically exchanging optimal codons for synonymous codons in the tuf genes we quantified the selective advantage of biased codon usage in highly expressed genes to be in the range 0.2–4.2 x 10⁻⁴ per codon per generation. These data quantify for the first time the potential for selection on synonymous codon choice to drive genome-wide sequence evolution in bacteria, and in particular to optimize the sequences of highly expressed genes. This quantification may have predictive applications in the design of synthetic genes and for heterologous gene expression in biotechnology.     

Codon Usage Bias and Mutation Constraints Reduce the Level of ErrorMinimization of the Genetic Code

Studies on the origin of the genetic code compare measures of the degree of error minimization of the standard code with measures produced by random variant codes but do not take into account codon usage, which was probably highly biased during the origin of the code. Codon usage bias could play an important role in the minimization of the chemical distances between amino acids because the importance of errors depends also on the frequency of the different codons. Here I show that when codon usage is taken into account, the degree of error minimization of the standard code may be dramatically reduced, and shifting to alternative codes often increases the degree of error minimization. This is especially true with a high CG content, which was probably the case during the origin of the code. I also show that the frequency of codes that perform better than the standard code, in terms of relative efficiency, is much higher in the neighborhood of the standard code itself, even when not considering codon usage bias; therefore alternative codes that differ only slightly from the standard code are more likely to evolve than some previous analyses suggested. My conclusions are that the standard genetic code is far from being an optimum with respect to error minimization and must have arisen for reasons other than error minimization.[Reviewing Editor: Martin Kreitman]     

Parallel evolution of the genetic code in arthropod mitochondrial genomes

The genetic code provides the translation table necessary to transform the information contained in DNA into the language of proteins. In this table, a correspondence between each codon and each amino acid is established: tRNA is the main adaptor that links the two. Although the genetic code is nearly universal, several variants of this code have been described in a wide range of nuclear and organellar systems, especially in metazoan mitochondria. These variants are generally found by searching for conserved positions that consistently code for a specific alternative amino acid in a new species. We have devised an accurate computational method to automate these comparisons, and have tested it with 626 metazoan mitochondrial genomes. Our results indicate that several arthropods have a new genetic code and translate the codon AGG as lysine instead of serine (as in the invertebrate mitochondrial genetic code) or arginine (as in the standard genetic code). We have investigated the evolution of the genetic code in the arthropods and found several events of parallel evolution in which the AGG codon was reassigned between serine and lysine. Our analyses also revealed correlated evolution between the arthropod genetic codes and the tRNA-Lys/-Ser, which show specific point mutations at the anticodons. These rather simple mutations, together with a low usage of the AGG codon, might explain the recurrence of the AGG reassignments.     

Driving change: the evolution of alternative genetic codes

Pioneering studies in the 1960s that elucidated the genetic code suggested that all extant forms of life use the same genetic code. This early presumption has subsequently been challenged by the discovery of deviations of the universal genetic code in prokaryotes, eukaryotic nuclear genomes and mitochondrial genomes. These studies have revealed that the genetic code is still evolving despite strong negative forces working against the fixation of mutations that result in codon reassignment. Recent data from in vitro, in vivo and in silico comparative genomics studies are revealing significant, previously overlooked links between modified nucleosides in tRNAs, genetic code ambiguity, genome base composition, codon usage and codon reassignment.     

A large-scale analysis of codon usage bias in 4868 bacterial genomes shows association of codon adaptation index with GC content,protein functional domains and bacterial phenotypes

Multiple synonymous codons code for the same amino acid, resulting in the degeneracy of the genetic code and in the preferred used of some codons called codon bias usage (CBU). We performed a large-scale analysis of codon usage bias analysing the distribution of the codon adaptation index (CAI) and the codon relative adaptiveness index (RA) in 4868 bacterial genomes. We found that CAI values differ significantly between protein functional domains and part of the protein outside domains and show how CAI, GC content and preferred usage of polymerase III alpha subunits are related. Additionally, we give evidence of the association between CAI and bacterial phenotypes.     

Theory of degenerate coding and informational parameters of protein coding genes

The theory of degenerate coding is presented in a way enabling further application to molecular biology. There are two kinds of redundancy of a degenerate code. The first is due to the excess in codon length and the second to the code degeneracy. If the code is asymmetrically degenerate, the second kind of redundancy can be profitable for control of error rate. This control can be performed just by selective synonymous codon usage. Utilisation of the genetic code is partially influenced by this theoretical possibility. In particular the degree of error protectivity is well correlated with deviation from equiprobability in synonymous codon usage. The biological significance of this fact is discussed.     

Codon Usage Decreases the Error Minimization Within the Genetic Code

The genetic code is not random but instead is organized in such a way that single nucleotide substitutions are more likely to result in changes between similar amino acids. This fidelity, or error minimization, has been proposed to be an adaptation within the genetic code. Many models have been proposed to measure this adaptation within the genetic code. However, we find that none of these consider codon usage differences between species. Furthermore, use of different indices of amino acid physicochemical characteristics leads to different estimations of this adaptation within the code. In this study, we try to establish a more accurate model to address this problem. In our model, a weighting scheme is established for mistranslation biases of the three different codon positions, transition/transversion biases, and codon usage. Different indices of amino acids physicochemical characteristics are also considered. In contrast to pervious work, our results show that the natural genetic code is not fully optimized for error minimization. The genetic code, therefore, is not the most optimized one for error minimization, but one that balances between flexibility and fidelity for different species.     

SCUMBLE: a method for systematic and accurate detection of codon usage bias by maximum likelihood estimation

The genetic code is degenerate—most amino acids can be encoded by from two to as many as six different codons. The synonymous codons are not used with equal frequency: not only are some codons favored over others, but also their usage can vary significantly from species to species and between different genes in the same organism. Known causes of codon bias include differences in mutation rates as well as selection pressure related to the expression level of a gene, but the standard analysis methods can account for only a fraction of the observed codon usage variation. We here introduce an explicit model of codon usage bias, inspired by statistical physics. Combining this model with a maximum likelihood approach, we are able to clearly identify different sources of bias in various genomes. We have applied the algorithm to Saccharomyces cerevisiae as well as 325 prokaryote genomes, and in most cases our model explains essentially all observed variance.     

Codon usage in Homo sapiens: evidence for a coding pattern on the non-coding strand and evolutionary implications of dinucleotide discrimination

This study reports the analysis of codon usage in 35 complete Homo sapiens genes. Both codon frequency and inter-codon interference exhibit patterns of evolutionary interest. There is a significant positive correlation between the frequency with which a given codon is used and the frequency with which its complement is used. Since the frequency of appearance of the complementary codon on the coding strand is equal to the frequency of appearance of the original codon on the non-coding strand, in the same phase, the non-coding strand is found to resemble the coding strand in triplet composition. The same effect has been observed in Escherichia coli. This preference for the use of certain complementary triplets as codons suggests that the evolution of the use of the genetic code depended to some extent upon the double-stranded nature of the coding material. In addition, the effect of discrimination against the use of two dinucleotides, CpG and UpA, is observed in codon usage and also in adjacent codon interference. Codons beginning with G, or A, are unlikely to be preceded by codons ending in C, or U, respectively. Consideration of codon assignment in the genetic code together with the observed CpG infrequency suggests that the evolution of the code may have been influenced by conditions in which the use of CpG dinucleotides was unfavorable. The infrequent use of UpA dinucleotides can be explained as the result of frameshift mutation during gene evolution.     

Factors affecting mito-nuclear codon usage interactions in the OXPHOS system of Drosophila melanogaster

Codon usage bias varies considerably among genomes and even within the genes of the same genome.In eukaryotic organisms,energy production in the form of oxidative phosphorylation(OXPHOS)is the only process under control of both nuclear and mitochondrial genomes.Although factors affecting codon usage in a single genome have been studied,this has not occurred when both interactional genomes are involved.Consequently, we investigated whether or not other factors influence codon usage of coevolved genes.We used Drosophila melanogaster as a model organism.Our χ2 test on the number of codons of nuclear and mitochondrial genes involved in the OXPHOS system was significantly different (χ2=7945.16,P<0.01).A plot of effective number of codons against GC3s content of nuclear genes showed that few genes lie on the expected curve,indicating that codon usage was random.Correspondence analysis indicated a significant correlation between axis 1 and codon adaptation index(R=0.947,P<0.01)in every nuclear gene sequence.Thus,codon usage bias of nuclear genes appeared to be affected by translational selection.Correlation between axis 1 coordinates and GC content(R=0.814.P<0.01)indicated that the codon usage of nuclear genes was also affected by GC composition.Analysis of mitochondrial genes did not reveal a significant correlation between axis 1 and any parameter.Statistical analyses indicated that codon usages of both nDNA and mtDNA were subjected to context-dependent mutations.     

Natural history and experimental evolution of the genetic code

The standard genetic code is a set of rules that relates the 20 canonical amino acids in proteins to groups of three bases in the mRNA. It evolved from a more primitive form and the attempts to reconstruct its natural history are based on its present-day features. Genetic code engineering as a new research field was developed independently in a few laboratories during the last 15 years. The main intention is to re-program protein synthesis by expanding the coding capacities of the genetic code via re-assignment of specific codons to un-natural amino acids. This article focuses on the question as to which extent hypothetical scenarios that led to codon re-assignments during the evolution of the genetic code are relevant for its further evolution in the laboratory. Current attempts to engineer the genetic code are reviewed with reference to theoretical works on its natural history. Integration of the theoretical considerations into experimental concepts will bring us closer to designer cells with target-engineered genetic codes that should open not only tremendous possibilities for the biotechnology of the twenty-first century but will also provide a basis for the design of novel life forms.     

Codon usage in bacteria: correlation with gene expressivity

The nucleic acid sequence bank now contains over 600 protein coding genes of which 107 are from prokaryotic organisms. Codon frequencies in each new prokaryotic gene are given. Analysis of genetic code usage in the 83 sequenced genes of the Escherichia coli genome (chromosome, transposons and plasmids) is presented, taking into account new data on gene expressivity and regulation as well as iso-tRNA specificity and cellular concentration. The codon composition of each gene is summarized using two indexes: one is based on the differential usage of iso-tRNA species during gene translation, the other on choice between Cytosine and Uracil for third base. A strong relationship between codon composition and mRNA expressivity is confirmed, even for genes transcribed in the same operon. The influence of codon use of peptide elongation rate and protein yield is discussed. Finally, the evolutionary aspect of codon selection in mRNA sequences is studied.     

The genetic code--40 years on

The genetic code discovered 40 years ago, consists of 64 triplets (codons) of nucleotides. The genetic code is almost universal. The same codons are assigned to the same amino acids and to the same START and STOP signals in the vast majority of genes in animals, plants, and microorganisms. Each codon encodes for one of the 20 amino acids used in the synthesis of proteins. That produces some redundancy in the code and most of the amino acids being encoded by more than one codon. The two cases have been found where selenocysteine or pyrrolysine, that are not one of the standard 20 is inserted by a tRNA into the growing polypeptide.     

Some theoretical aspects of reprogramming the standard genetic code

Reprogramming of the standard genetic code to include non-canonical amino acids (ncAAs) opens new prospects for medicine, industry, and biotechnology. There are several methods of code engineering, which allow us for storing new genetic information in DNA sequences and producing proteins with new properties. Here, we provided a theoretical background for the optimal genetic code expansion, which may find application in the experimental design of the genetic code. We assumed that the expanded genetic code includes both canonical and non-canonical information stored in 64 classical codons. What is more, the new coding system is robust to point mutations and minimizes the possibility of reversion from the new to old information. In order to find such codes, we applied graph theory to analyze the properties of optimal codon sets. We presented the formal procedure in finding the optimal codes with various number of vacant codons that could be assigned to new amino acids. Finally, we discussed the optimal number of the newly incorporated ncAAs and also the optimal size of codon groups that can be assigned to ncAAs.     

The 'effective number of codons' used in a gene

A simple measure is presented that quantifies how far the codon usage of a gene departs from equal usage of synonymous codons. This measure of synonymous codon usage bias, the 'effective number of codons used in a gene', Nc, can be easily calculated from codon usage data alone, and is independent of gene length and amino acid (aa) composition. Nc can take values from 20, in the case of extreme bias where one codon is exclusively used for each aa, to 61 when the use of alternative synonymous codons is equally likely. Nc thus provides an intuitively meaningful measure of the extent of codon preference in a gene. Codon usage patterns across genes can be investigated by the Nc-plot: a plot of Nc vs. G + C content at synonymous sites. Nc-plots are produced for Homo sapiens, Saccharomyces cerevisiae, Escherichia coli, Bacillus subtilis, Dictyostelium discoideum, and Drosophila melanogaster. A FORTRAN77 program written to calculate Nc is available on request.     

In vitro selection for sense codon suppression

The universal genetic code links the 20 naturally occurring amino acids to the 61 sense codons. Previously, the UAG amber stop codon (a nonsense codon) has been used as a blank in the code to insert natural and unnatural amino acids via nonsense suppression. We have developed a selection methodology to investigate whether the unnatural amino acid biocytin could be incorporated into an mRNA display library at sense codons. In these experiments we probed a single randomized NNN codon with a library of 16 orthogonal, biocytin-acylated tRNAs. In vitro selection for efficient incorporation of the unnatural amino acid resulted in templates containing the GUA codon at the randomized position. This sense suppression occurs via Watson-Crick pairing with similar efficiency to UAG-mediated nonsense suppression. These experiments suggest that sense codon suppression is a viable means to expand the chemical and functional diversity of the genetic code.     

Analysis of the codon usage pattern in the Vibrio cholerae genome.

The codon usage in the Vibrio cholerae genome is analyzed in this paper. Although there are much more genes on the chromosome 1 than on chromosome 2, the codon usage patterns of genes on the two chromosomes are quite similar, indicating that the two chromosomes may have coexisted in the same cell for a very long history. Unlike the base frequency pattern observed in other genomes, the G+C content at the third codon position of the V. cholerae genome varies in a rather small interval. The most notable feature of codon usage of V. cholerae genome is that there is a fraction of genes show significant bias in base choice at the second codon position. The 2,006 known genes can be classified into two clusters according to the base frequencies at this position. The smaller cluster contains 227 genes, most of which code for proteins involved in transport and binding functions. The encoding products of these genes have significant bias in amino acids composition as compared with other genes. The codon usage patterns for the 1,836 function unknown ORFs are also analyzed, which is useful to study their functions.     

The new classification scheme of the genetic code, its early evolution, and tRNA usage

We present a new classification scheme of the genetic code. In contrast to the standard form it clearly shows five codon symmetries: codon-anticodon, codon-reverse codon, and sense-antisense symmetry, as well as symmetries with respect to purine-pyrimidine (A versus G, U versus C) and keto-aminobase (G versus U, A versus C) exchanges. We study the number of tRNA genes of 16 archaea, 81 bacteria and 7 eucaryotes to analyze whether these symmetries are reflected in the corresponding tRNA usage patterns. Two features are especially striking: reverse stop codons do not have their own tRNAs (just one exception in human), and A** anticodons are significantly suppressed. Our classification scheme of the genetic code and the identified tRNA usage patterns support recent speculations about the early evolution of the genetic code. In particular, pre-tRNAs might have had the ability to bind their codons in two directions to the corresponding codons.