Models of amino acid substitution and applications to mitochondrial protein evolution

Models of amino acid substitution were developed and compared using maximum likelihood. Two kinds of models are considered. "Empirical" models do not explicitly consider factors that shape protein evolution, but attempt to summarize the substitution pattern from large quantities of real data. "Mechanistic" models are formulated at the codon level and separate mutational biases at the nucleotide level from selective constraints at the amino acid level. They account for features of sequence evolution, such as transition-transversion bias and base or codon frequency biases, and make use of physicochemical distances between amino acids to specify nonsynonymous substitution rates. A general approach is presented that transforms a Markov model of codon substitution into a model of amino acid replacement. Protein sequences from the entire mitochondrial genomes of 20 mammalian species were analyzed using different models. The mechanistic models were found to fit the data better than empirical models derived from large databases. Both the mutational distance between amino acids (determined by the genetic code and mutational biases such as the transition-transversion bias) and the physicochemical distance are found to have strong effects on amino acid substitution rates. A significant proportion of amino acid substitutions appeared to have involved more than one codon position, indicating that nucleotide substitutions at neighboring sites may be correlated. Rates of amino acid substitution were found to be highly variable among sites.      

On the organizational dynamics of the genetic code

The organization of the canonical genetic code needs to be thoroughly illuminated. Here we reorder the four nucleotides-adenine, thymine, guanine and cytosine-according to their emergence in evolution, and apply the organizational rules to devising an algebraic representation for the canonical genetic code. Under a framework of the devised code, we quantify codon and amino acid usages from a large collection of 917 prokaryotic genome sequences, and associate the usages with its intrinsic structure and classification schemes as well as amino acid physicochemical properties. Our results show that the algebraic representation of the code is structurally equivalent to a content-centric organization of the code and that codon and amino acid usages under different classification schemes were correlated closely with GC content, implying a set of rules governing composition dynamics across a wide variety of prokaryotic genome sequences. These results also indicate that codons and amino acids are not randomly allocated in the code, where the six-fold degenerate codons and their amino acids have important balancing roles for error minimization. Therefore, the content-centric code is of great usefulness in deciphering its hitherto unknown regularities as well as the dynamics of nucleotide, codon, and amino acid compositions.     

Organization of the mitochondrial genome of Atlantic cod, Gadus morhua.

The mitochondrial DNA (mtDNA) from the Atlantic cod, Gadus morhua, was mapped using 11 different restriction enzymes and cloned into plasmid vectors. Sequence data obtained from more than 10 kilobases of cod mtDNA show that the genome organization, genetic code, and the overall codon usage have been conserved throughout the evolution of vertebrates. Comparison of the derived amino acid sequences of proteins encoded by cod mtDNA to the ones encoded by Xenopus laevis mtDNA revealed that the amino acid identity range from 46% to 93% for the different proteins. ND4L is most divergent while COI is most conserved. GUG was found as the translation initiation codon of the COI gene, indicating a dual coding function for this codon. The sequences of the 997 base pair displacement-loop (D-loop)-containing region and the origin of L-strand replication (oriL), are presented. Only few of the primary and secondary structure features found to be conserved among mammalian mitochondrial D-loops, can be identified in cod. Presence of CSB-2 in the D-loop-containing region and the conserved hairpin structure at oriL, indicates that replication of bony fish mtDNA may follow the same general scheme as described for higher vertebrates.     

Prokaryotic gene finding based on physicochemical characteristics of codons calculated from molecular dynamics simulations

An ab initio model for gene prediction in prokaryotic genomes is proposed based on physicochemical characteristics of codons calculated from molecular dynamics (MD) simulations. The model requires a specification of three calculated quantities for each codon: the double-helical trinucleotide base pairing energy, the base pair stacking energy, and an index of the propensity of a codon for protein-nucleic acid interactions. The base pairing and stacking energies for each codon are obtained from recently reported MD simulations on all unique tetranucleotide steps, and the third parameter is assigned based on the conjugate rule previously proposed to account for the wobble hypothesis with respect to degeneracies in the genetic code. The third interaction propensity parameter values correlate well with ab initio MD calculated solvation energies and flexibility of codon sequences as well as codon usage in genes and amino acid composition frequencies in ∼175,000 protein sequences in the Swissprot database. Assignment of these three parameters for each codon enables the calculation of the magnitude and orientation of a cumulative three-dimensional vector for a DNA sequence of any length in each of the six genomic reading frames. Analysis of 372 genomes comprising ∼350,000 genes shows that the orientations of the gene and nongene vectors are well differentiated and make a clear distinction feasible between genic and nongenic sequences at a level equivalent to or better than currently available knowledge-based models trained on the basis of empirical data, presenting a strong support for the possibility of a unique and useful physicochemical characterization of DNA sequences from codons to genomes.     

Entropy of the genetic information and evolution.

The entropy of the amino acid sequences coded by DNA is considered as a measure of diversity of variety of proteins, and is taken as a measure of evolution. The DNA or m-RNA sequence is considered as a stationary second-order Markov chain composed of four kinds of bases. Because of the biased nature of the genetic code table, increase of entropy of amino acid sequences is possible with biased nucleotide sequence. Thus the biased DNA base composition and the extreme rarity of the base doublet CpG of higher organisms are explained. It is expected that the amino acid composition was highly biased at the days of the origin of the genetic code table, and the more frequent amino acids have tended to get rarer, and the rarer ones more frequent. This tendency is observed in the evolution of hemoglobin, cytochrome C, fibrinopeptide, immunoglobulin and lysozyme, and protein as a whole.     

A statistical test of hypotheses on the organization and origin of the genetic code

Summary Theories of the origin of the genetic code assign different weights to amino acid properties such as polarity and precursor-product relationship. Previous statistical work on the origin of the genetic code has produced controversial results. We analyze relationships between various amino acid and tRNA properties by one and the same statistical method. It is shown that polarities as well as precursor-product relationships are both likely to have been important in shaping the genetic code, together with codon swapping that left protein sequences intact.     

Selection on Codon Usage for Error Minimization at the Protein Level

Given the structure of the genetic code, synonymous codons differ in their capacity to minimize the effects of errors due to mutation or mistranslation. I suggest that this may lead, in protein-coding genes, to a preference for codons that minimize the impact of errors at the protein level. I develop a theoretical measure of error minimization for each codon, based on amino acid similarity. This measure is used to calculate the degree of error minimization for 82 genes of Drosophila melanogaster and 432 rodent genes and to study its relationship with CG content, the degree of codon usage bias, and the rate of nucleotide substitution. I show that (i) Drosophila and rodent genes tend to prefer codons that minimize errors; (ii) this cannot be merely the effect of mutation bias; (iii) the degree of error minimization is correlated with the degree of codon usage bias; (iv) the amino acids that contribute more to codon usage bias are the ones for which synonymous codons differ more in the capacity to minimize errors; and (v) the degree of error minimization is correlated with the rate of nonsynonymous substitution. These results suggest that natural selection for error minimization at the protein level plays a role in the evolution of coding sequences in Drosophila and rodents.Reviewing Editor: Dr. Massimo Di Giulio     

Stereochemical origins of the genetic code

The origin of the genetic code may be attributed to a postulated prebiological stereochemistry in which amino acid dimers, the trans -R,R'-diketopiperazines, interacted with prototype codon and anticodon nucleotide sequences. An intricately coupled stereochemistry is formulated which displays a binary logic for amino acid-codon recognition. It is shown that the diketopiperazine ring system can be inserted between any terminal pair of base paired nucleotides in a codon-anticodon structure with exact registration of complementary hydrogen bonding functional groups. This yields a codon-dimer-anticodon structure in which each amino acid residue is projected towards and interacts with a particular sequence of vicinal nucleotides on either codon or anticodon. The projection direction and the sequence of nucleotides encountered is a strongly coupled function of the choice of codon terminal nucleotide and the handedness of the amino acid. The reciprocal chemical nature of the complementary base pairs drives the selection of dimers containing quite dissimilar and chirally opposed amino acids. Application of the stereochemical model to the in vivo system leads to a general correlation for amino acid-codon assignments. The genetic code is restated in terms of the dimers selected. The profound symmetry of the code is elucidated and this proves useful for correlative and predictive purposes.     

Structural Phylogenomics Retrodicts the Origin of the Genetic Code and Uncovers the Evolutionary Impact of Protein Flexibility

The genetic code shapes the genetic repository. Its origin has puzzled molecular scientists for over half a century and remains a long-standing mystery. Here we show that the origin of the genetic code is tightly coupled to the history of aminoacyl-tRNA synthetase enzymes and their interactions with tRNA. A timeline of evolutionary appearance of protein domain families derived from a structural census in hundreds of genomes reveals the early emergence of the ‘operational’ RNA code and the late implementation of the standard genetic code. The emergence of codon specificities and amino acid charging involved tight coevolution of aminoacyl-tRNA synthetases and tRNA structures as well as episodes of structural recruitment. Remarkably, amino acid and dipeptide compositions of single-domain proteins appearing before the standard code suggest archaic synthetases with structures homologous to catalytic domains of tyrosyl-tRNA and seryl-tRNA synthetases were capable of peptide bond formation and aminoacylation. Results reveal that genetics arose through coevolutionary interactions between polypeptides and nucleic acid cofactors as an exacting mechanism that favored flexibility and folding of the emergent proteins. These enhancements of phenotypic robustness were likely internalized into the emerging genetic system with the early rise of modern protein structure.     

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.     

Entropy of the genetic information and evolution

The entropy of the amino acid sequences coded by DNA is considered as a measure of diversity or variety of proteins, and is taken as a measure of evolution. The DNA or m-RNA sequence is corsidered as a stationary second-order Markov chain composed of four kinds of bases. Because of the biased nature of the genetic code table, increase of entropy of amino acid sequences is possible with biased nucleotide sequence. Thus the biased DNA base composition and the extreme rarity of the base doubletC _p G of higher organisms are explained. It is expected that the amino acid composition was highly biased at the days of the origin of the genetic code table, and the more frequent amino acids have tended to get rarer, and the rarer ones more frequent. This tendency is observed in the evolution of hemoglobin, cytochrome C, fibrinopeptide, immunoglobulin and lysozyme, and protein as a whole.     

An empirical codon model for protein sequence evolution

In the past, 2 kinds of Markov models have been considered to describe protein sequence evolution. Codon-level models have been mechanistic with a small number of parameters designed to take into account features, such as transition-transversion bias, codon frequency bias, and synonymous-nonsynonymous amino acid substitution bias. Amino acid models have been empirical, attempting to summarize the replacement patterns observed in large quantities of data and not explicitly considering the distinct factors that shape protein evolution. We have estimated the first empirical codon model (ECM). Previous codon models assume that protein evolution proceeds only by successive single nucleotide substitutions, but our results indicate that model accuracy is significantly improved by incorporating instantaneous doublet and triplet changes. We also find that the affiliations between codons, the amino acid each encodes and the physicochemical properties of the amino acids are main factors driving the process of codon evolution. Neither multiple nucleotide changes nor the strong influence of the genetic code nor amino acids' physicochemical properties form a part of standard mechanistic models and their views of how codon evolution proceeds. We have implemented the ECM for likelihood-based phylogenetic analysis, and an assessment of its ability to describe protein evolution shows that it consistently outperforms comparable mechanistic codon models. We point out the biological interpretation of our ECM and possible consequences for studies of selection.     

Challenges of the genetic code for exploring sequence space in directed protein evolution

Directed protein evolution is the most versatile method for studying protein structure–function relationships, and for tailoring a protein's properties to the needs of industrial applications. In this review, we performed a statistical analysis on the genetic code to study the extent and consequence of the organization of the genetic code on amino acid substitution patterns generated in directed evolution experiments. In detail, we analyzed amino acid substitution patterns caused by (a) a single nucleotide (nt) exchange at each position of all 64 codons, and (b) two subsequent nt exchanges (first and second nt, first and third nt, second and third nt). Additionally, transitions and transversions mutations were compared at the level of amino acid substitution patterns. The latter analysis showed that single nucleotide substitution in a codon generates only 39.5% of the natural diversity on the protein level with 5.2–7 amino acid substitutions per codon. Transversions generate more complex amino acid substitution patterns (increased number and chemically more diverse amino acid substitutions) than transitions. Simultaneous nt exchanges at both first and second nt of a codon generates very diverse amino acid substitution patterns, achieving 83.2% of the natural diversity. The statistical analysis described in this review sets the objectives for novel random mutagenesis methods that address the consequences of the organization of the genetic code. Random mutagenesis methods that favor transversions or introduce consecutive nt exchanges can contribute in this regard.     

Noncanonical amino acid mutagenesis in response to recoding signal-enhanced quadruplet codons

While amber suppression is the most common approach to introduce noncanonical amino acids into proteins in live cells, quadruplet codon decoding has potential to enable a greatly expanded genetic code with up to 256 new codons for protein biosynthesis. Since triplet codons are the predominant form of genetic code in nature, quadruplet codon decoding often displays limited efficiency. In this work, we exploited a new approach to significantly improve quadruplet UAGN and AGGN (N = A, U, G, C) codon decoding efficiency by using recoding signals imbedded in mRNA. With representative recoding signals, the expression level of mutant proteins containing UAGN and AGGN codons reached 48% and 98% of that of the wild-type protein, respectively. Furthermore, this strategy mitigates a common concern of reading-through endogenous stop codons with amber suppression-based system. Since synthetic recoding signals are rarely found near the endogenous UAGN and AGGN sequences, a low level of undesirable suppression is expected. Our strategy will greatly enhance the utility of noncanonical amino acid mutagenesis in live-cell studies.     

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]     

RNA-ligand chemistry: a testable source for the genetic code

In the genetic code, triplet codons and amino acids can be shown to be related by chemical principles. Such chemical regularities could be created either during the code's origin or during later evolution. One such chemical principle can now be shown experimentally. Natural or particularly selected RNA binding sites for at least three disparate amino acids (arginine, isoleucine, and tyrosine) are enriched in codons for the cognate amino acid. Currently, in 517 total nucleotides, binding sites contain 2.4-fold more codon sequences than surrounding nucleotides. The aggregate probability of this enrichment is 10(-7) to 10(-8), had codons and binding site sequences been independent. Thus, at least some primordial coding assignments appear to have exploited triplets from amino acid binding sites as codons.     

Challenges of the genetic code for exploring sequence space in directed protein evolution

Directed protein evolution is the most versatile method for studying protein structure-function relationships, and for tailoring a protein's properties to the needs of industrial applications. In this review, we performed a statistical analysis on the genetic code to study the extent and consequence of the organization of the genetic code on amino acid substitution patterns generated in directed evolution experiments. In detail, we analyzed amino acid substitution patterns caused by (a) a single nucleotide (nt) exchange at each position of all 64 codons, and (b) two subsequent nt exchanges (first and second nt, first and third nt, second and third nt). Additionally, transitions and transversions mutations were compared at the level of amino acid substitution patterns. The latter analysis showed that single nucleotide substitution in a codon generates only 39.5% of the natural diversity on the protein level with 5.2-7 amino acid substitutions per codon. Transversions generate more complex amino acid substitution patterns (increased number and chemically more diverse amino acid substitutions) than transitions. Simultaneous nt exchanges at both first and second nt of a codon generates very diverse amino acid substitution patterns, achieving 83.2% of the natural diversity. The statistical analysis described in this review sets the objectives for novel random mutagenesis methods that address the consequences of the organization of the genetic code. Random mutagenesis methods that favor transversions or introduce consecutive nt exchanges can contribute in this regard.     

A biophysical basis for the emergence of the genetic code in protocells

The origin of the genetic code is an abiding mystery in biology. Hints of a ‘code within the codons’ suggest biophysical interactions, but these patterns have resisted interpretation. Here, we present a new framework, grounded in the autotrophic growth of protocells from CO₂ and H₂. Recent work suggests that the universal core of metabolism recapitulates a thermodynamically favoured protometabolism right up to nucleotide synthesis. Considering the genetic code in relation to an extended protometabolism allows us to predict most codon assignments. We show that the first letter of the codon corresponds to the distance from CO₂ fixation, with amino acids encoded by the purines (G followed by A) being closest to CO₂ fixation. These associations suggest a purine-rich early metabolism with a restricted pool of amino acids. The second position of the anticodon corresponds to the hydrophobicity of the amino acid encoded. We combine multiple measures of hydrophobicity to show that this correlation holds strongly for early amino acids but is weaker for later species. Finally, we demonstrate that redundancy at the third position is not randomly distributed around the code: non-redundant amino acids can be assigned based on size, specifically length. We attribute this to additional stereochemical interactions at the anticodon. These rules imply an iterative expansion of the genetic code over time with codon assignments depending on both distance from CO₂ and biophysical interactions between nucleotide sequences and amino acids. In this way the earliest RNA polymers could produce non-random peptide sequences with selectable functions in autotrophic protocells.